diff --git a/src/available_models.py b/src/available_models.py
index cc1e2e7..18bd043 100644
--- a/src/available_models.py
+++ b/src/available_models.py
@@ -1,3 +1,3 @@
 # available_models.py
 # There's no API for this, sorry
-available_models = {"llama3": {"description": "Meta Llama 3: The most capable openly available LLM to date", "tags": ["latest", "70b", "8b", "instruct", "text", "70b-instruct", "70b-text", "70b-instruct-q4_0", "70b-instruct-q4_1", "70b-instruct-q5_0", "70b-instruct-q5_1", "70b-instruct-q8_0", "70b-instruct-q2_K", "70b-instruct-q3_K_S", "70b-instruct-q3_K_M", "70b-instruct-q3_K_L", "70b-instruct-q4_K_S", "70b-instruct-q4_K_M", "70b-instruct-q5_K_S", "70b-instruct-q5_K_M", "70b-instruct-q6_K", "70b-instruct-fp16", "70b-text-q4_0", "70b-text-q4_1", "70b-text-q5_0", "70b-text-q5_1", "70b-text-q8_0", "70b-text-q2_K", "70b-text-q3_K_S", "70b-text-q3_K_M", "70b-text-q3_K_L", "70b-text-q4_K_S", "70b-text-q4_K_M", "70b-text-q5_K_S", "70b-text-q5_K_M", "70b-text-q6_K", "70b-text-fp16", "8b-text", "8b-instruct-q4_0", "8b-instruct-q4_1", "8b-instruct-q5_0", "8b-instruct-q5_1", "8b-instruct-q8_0", "8b-instruct-q2_K", "8b-instruct-q3_K_S", "8b-instruct-q3_K_M", "8b-instruct-q3_K_L", "8b-instruct-q4_K_S", "8b-instruct-q4_K_M", "8b-instruct-q5_K_S", "8b-instruct-q5_K_M", "8b-instruct-q6_K", "8b-instruct-fp16", "8b-text-q4_0", "8b-text-q4_1", "8b-text-q5_0", "8b-text-q5_1", "8b-text-q8_0", "8b-text-q2_K", "8b-text-q3_K_S", "8b-text-q3_K_M", "8b-text-q3_K_L", "8b-text-q4_K_S", "8b-text-q4_K_M", "8b-text-q5_K_S", "8b-text-q6_K", "8b-text-fp16"]}, "phi3": {"description": "Phi-3 Mini is a 3.8B parameters, lightweight, state-of-the-art open model by Microsoft.", "tags": ["latest", "3.8b", "instruct", "mini", "3.8b-mini-instruct-4k-q4_K_M", "3.8b-mini-instruct-4k-fp16"]}, "wizardlm2": {"description": "State of the art large language model from Microsoft AI with improved performance on complex chat, multilingual, reasoning and agent use cases.", "tags": ["latest", "8x22b", "7b", "8x22b-q4_0", "8x22b-q8_0", "8x22b-q2_K", "8x22b-fp16", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "mistral": {"description": "The 7B model released by Mistral AI, updated to version 0.2.", "tags": ["latest", "7b", "instruct", "text", "v0.1", "v0.2", "7b-instruct", "7b-text", "7b-instruct-q4_0", "7b-instruct-q4_1", "7b-instruct-q5_0", "7b-instruct-q5_1", "7b-instruct-q8_0", "7b-instruct-q2_K", "7b-instruct-q3_K_S", "7b-instruct-q3_K_M", "7b-instruct-q3_K_L", "7b-instruct-q4_K_S", "7b-instruct-q4_K_M", "7b-instruct-q5_K_S", "7b-instruct-q5_K_M", "7b-instruct-q6_K", "7b-instruct-fp16", "7b-text-q4_0", "7b-text-q4_1", "7b-text-q5_0", "7b-text-q5_1", "7b-text-q8_0", "7b-text-q2_K", "7b-text-q3_K_S", "7b-text-q3_K_M", "7b-text-q3_K_L", "7b-text-q4_K_S", "7b-text-q4_K_M", "7b-text-q5_K_S", "7b-text-q5_K_M", "7b-text-q6_K", "7b-text-fp16", "7b-instruct-v0.2-q4_0", "7b-instruct-v0.2-q4_1", "7b-instruct-v0.2-q5_0", "7b-instruct-v0.2-q5_1", "7b-instruct-v0.2-q8_0", "7b-instruct-v0.2-q2_K", "7b-instruct-v0.2-q3_K_S", "7b-instruct-v0.2-q3_K_M", "7b-instruct-v0.2-q3_K_L", "7b-instruct-v0.2-q4_K_S", "7b-instruct-v0.2-q4_K_M", "7b-instruct-v0.2-q5_K_S", "7b-instruct-v0.2-q5_K_M", "7b-instruct-v0.2-q6_K", "7b-instruct-v0.2-fp16", "7b-text-v0.2-q4_0", "7b-text-v0.2-q4_1", "7b-text-v0.2-q5_0", "7b-text-v0.2-q5_1", "7b-text-v0.2-q8_0", "7b-text-v0.2-q2_K", "7b-text-v0.2-q3_K_S", "7b-text-v0.2-q3_K_M", "7b-text-v0.2-q3_K_L", "7b-text-v0.2-q4_K_S", "7b-text-v0.2-q4_K_M", "7b-text-v0.2-q5_K_S", "7b-text-v0.2-q5_K_M", "7b-text-v0.2-q6_K", "7b-text-v0.2-fp16"]}, "gemma": {"description": "Gemma is a family of lightweight, state-of-the-art open models built by Google DeepMind. Updated to version 1.1", "tags": ["latest", "7b", "2b", "instruct", "text", "v1.1", "7b-instruct", "7b-text", "7b-v1.1", "7b-instruct-q4_0", "7b-instruct-q4_1", "7b-instruct-q5_0", "7b-instruct-q5_1", "7b-instruct-q8_0", "7b-instruct-q2_K", "7b-instruct-q3_K_S", "7b-instruct-q3_K_M", "7b-instruct-q3_K_L", "7b-instruct-q4_K_S", "7b-instruct-q4_K_M", "7b-instruct-q5_K_S", "7b-instruct-q5_K_M", "7b-instruct-q6_K", "7b-instruct-fp16", "7b-text-q4_0", "7b-text-q4_1", "7b-text-q5_0", "7b-text-q5_1", "7b-text-q8_0", "7b-text-q2_K", "7b-text-q3_K_S", "7b-text-q3_K_M", "7b-text-q3_K_L", "7b-text-q4_K_S", "7b-text-q4_K_M", "7b-text-q5_K_S", "7b-text-q5_K_M", "7b-text-q6_K", "7b-text-fp16", "7b-instruct-v1.1-q4_0", "7b-instruct-v1.1-q4_1", "7b-instruct-v1.1-q5_0", "7b-instruct-v1.1-q5_1", "7b-instruct-v1.1-q8_0", "7b-instruct-v1.1-q2_K", "7b-instruct-v1.1-q3_K_S", "7b-instruct-v1.1-q3_K_M", "7b-instruct-v1.1-q3_K_L", "7b-instruct-v1.1-q4_K_S", "7b-instruct-v1.1-q4_K_M", "7b-instruct-v1.1-q5_K_S", "7b-instruct-v1.1-q5_K_M", "7b-instruct-v1.1-q6_K", "7b-instruct-v1.1-fp16", "2b-instruct", "2b-text", "2b-v1.1", "2b-instruct-q4_0", "2b-instruct-q4_1", "2b-instruct-q5_0", "2b-instruct-q5_1", "2b-instruct-q8_0", "2b-instruct-q2_K", "2b-instruct-q3_K_S", "2b-instruct-q3_K_M", "2b-instruct-q3_K_L", "2b-instruct-q4_K_S", "2b-instruct-q4_K_M", "2b-instruct-q5_K_S", "2b-instruct-q5_K_M", "2b-instruct-q6_K", "2b-instruct-fp16", "2b-text-q4_0", "2b-text-q4_1", "2b-text-q5_0", "2b-text-q5_1", "2b-text-q8_0", "2b-text-q2_K", "2b-text-q3_K_S", "2b-text-q3_K_M", "2b-text-q3_K_L", "2b-text-q4_K_S", "2b-text-q4_K_M", "2b-text-q5_K_S", "2b-text-q5_K_M", "2b-text-q6_K", "2b-text-fp16", "2b-instruct-v1.1-q4_0", "2b-instruct-v1.1-q4_1", "2b-instruct-v1.1-q5_0", "2b-instruct-v1.1-q5_1", "2b-instruct-v1.1-q8_0", "2b-instruct-v1.1-q2_K", "2b-instruct-v1.1-q3_K_S", "2b-instruct-v1.1-q3_K_M", "2b-instruct-v1.1-q3_K_L", "2b-instruct-v1.1-q4_K_S", "2b-instruct-v1.1-q4_K_M", "2b-instruct-v1.1-q5_K_S", "2b-instruct-v1.1-q5_K_M", "2b-instruct-v1.1-q6_K", "2b-instruct-v1.1-fp16"]}, "mixtral": {"description": "A set of Mixture of Experts (MoE) model with open weights by Mistral AI in 8x7b and 8x22b parameter sizes.", "tags": ["latest", "8x22b", "8x7b", "instruct", "text", "v0.1", "8x22b-instruct", "8x22b-text", "8x7b-instruct-v0.1-q4_0", "8x22b-instruct-v0.1-q4_0", "8x7b-instruct-v0.1-q4_1", "8x22b-instruct-v0.1-q4_1", "8x22b-instruct-v0.1-q5_0", "8x7b-instruct-v0.1-q5_0", "8x7b-instruct-v0.1-q5_1", "8x22b-instruct-v0.1-q5_1", "8x22b-instruct-v0.1-q8_0", "8x7b-instruct-v0.1-q8_0", "8x7b-instruct-v0.1-q2_K", "8x22b-instruct-v0.1-q2_K", "8x7b-instruct-v0.1-q3_K_S", "8x22b-instruct-v0.1-q3_K_S", "8x22b-instruct-v0.1-q3_K_M", "8x7b-instruct-v0.1-q3_K_M", "8x22b-instruct-v0.1-q3_K_L", "8x7b-instruct-v0.1-q3_K_L", "8x22b-instruct-v0.1-q4_K_S", "8x7b-instruct-v0.1-q4_K_S", "8x7b-instruct-v0.1-q4_K_M", "8x22b-instruct-v0.1-q4_K_M", "8x22b-instruct-v0.1-q5_K_S", "8x7b-instruct-v0.1-q5_K_S", "8x7b-instruct-v0.1-q5_K_M", "8x22b-instruct-v0.1-q5_K_M", "8x22b-instruct-v0.1-q6_K", "8x7b-instruct-v0.1-q6_K", "8x22b-instruct-v0.1-fp16", "8x7b-instruct-v0.1-fp16", "8x22b-text-v0.1-q4_0", "8x7b-text-v0.1-q4_0", "8x7b-text-v0.1-q4_1", "8x22b-text-v0.1-q4_1", "8x22b-text-v0.1-q5_0", "8x7b-text-v0.1-q5_0", "8x22b-text-v0.1-q5_1", "8x7b-text-v0.1-q5_1", "8x22b-text-v0.1-q8_0", "8x7b-text-v0.1-q8_0", "8x7b-text-v0.1-q2_K", "8x22b-text-v0.1-q2_K", "8x22b-text-v0.1-q3_K_S", "8x7b-text-v0.1-q3_K_S", "8x22b-text-v0.1-q3_K_M", "8x7b-text-v0.1-q3_K_M", "8x7b-text-v0.1-q3_K_L", "8x22b-text-v0.1-q3_K_L", "8x22b-text-v0.1-q4_K_S", "8x7b-text-v0.1-q4_K_S", "8x22b-text-v0.1-q4_K_M", "8x7b-text-v0.1-q4_K_M", "8x7b-text-v0.1-q5_K_S", "8x22b-text-v0.1-q5_K_S", "8x7b-text-v0.1-q5_K_M", "8x22b-text-v0.1-q5_K_M", "8x22b-text-v0.1-q6_K", "8x7b-text-v0.1-q6_K", "8x7b-text-v0.1-fp16", "8x22b-text-v0.1-fp16", "v0.1-instruct"]}, "llama2": {"description": "Llama 2 is a collection of foundation language models ranging from 7B to 70B parameters.", "tags": ["latest", "70b", "13b", "7b", "chat", "text", "70b-chat", "70b-text", "70b-chat-q4_0", "70b-chat-q4_1", "70b-chat-q5_0", "70b-chat-q5_1", "70b-chat-q8_0", "70b-chat-q2_K", "70b-chat-q3_K_S", "70b-chat-q3_K_M", "70b-chat-q3_K_L", "70b-chat-q4_K_S", "70b-chat-q4_K_M", "70b-chat-q5_K_S", "70b-chat-q5_K_M", "70b-chat-q6_K", "70b-chat-fp16", "70b-text-q4_0", "70b-text-q4_1", "70b-text-q5_0", "70b-text-q5_1", "70b-text-q8_0", "70b-text-q2_K", "70b-text-q3_K_S", "70b-text-q3_K_M", "70b-text-q3_K_L", "70b-text-q4_K_S", "70b-text-q4_K_M", "70b-text-q5_K_S", "70b-text-q5_K_M", "70b-text-q6_K", "70b-text-fp16", "13b-chat", "13b-text", "13b-chat-q4_0", "13b-chat-q4_1", "13b-chat-q5_0", "13b-chat-q5_1", "13b-chat-q8_0", "13b-chat-q2_K", "13b-chat-q3_K_S", "13b-chat-q3_K_M", "13b-chat-q3_K_L", "13b-chat-q4_K_S", "13b-chat-q4_K_M", "13b-chat-q5_K_S", "13b-chat-q5_K_M", "13b-chat-q6_K", "13b-chat-fp16", "13b-text-q4_0", "13b-text-q4_1", "13b-text-q5_0", "13b-text-q5_1", "13b-text-q8_0", "13b-text-q2_K", "13b-text-q3_K_S", "13b-text-q3_K_M", "13b-text-q3_K_L", "13b-text-q4_K_S", "13b-text-q4_K_M", "13b-text-q5_K_S", "13b-text-q5_K_M", "13b-text-q6_K", "13b-text-fp16", "7b-chat", "7b-text", "7b-chat-q4_0", "7b-chat-q4_1", "7b-chat-q5_0", "7b-chat-q5_1", "7b-chat-q8_0", "7b-chat-q2_K", "7b-chat-q3_K_S", "7b-chat-q3_K_M", "7b-chat-q3_K_L", "7b-chat-q4_K_S", "7b-chat-q4_K_M", "7b-chat-q5_K_S", "7b-chat-q5_K_M", "7b-chat-q6_K", "7b-chat-fp16", "7b-text-q4_0", "7b-text-q4_1", "7b-text-q5_0", "7b-text-q5_1", "7b-text-q8_0", "7b-text-q2_K", "7b-text-q3_K_S", "7b-text-q3_K_M", "7b-text-q3_K_L", "7b-text-q4_K_S", "7b-text-q4_K_M", "7b-text-q5_K_S", "7b-text-q5_K_M", "7b-text-q6_K", "7b-text-fp16"]}, "codegemma": {"description": "CodeGemma is a collection of powerful, lightweight models that can perform a variety of coding tasks like fill-in-the-middle code completion, code generation, natural language understanding, mathematical reasoning, and instruction following.", "tags": ["latest", "7b", "2b", "code", "instruct", "7b-code", "7b-instruct", "7b-v1.1", "7b-code-q4_0", "7b-code-q4_1", "7b-code-q5_0", "7b-code-q5_1", "7b-code-q8_0", "7b-code-q2_K", "7b-code-q3_K_S", "7b-code-q3_K_M", "7b-code-q3_K_L", "7b-code-q4_K_S", "7b-code-q4_K_M", "7b-code-q5_K_S", "7b-code-q5_K_M", "7b-code-q6_K", "7b-code-fp16", "7b-instruct-q4_0", "7b-instruct-q4_1", "7b-instruct-q5_0", "7b-instruct-q5_1", "7b-instruct-q8_0", "7b-instruct-q2_K", "7b-instruct-q3_K_S", "7b-instruct-q3_K_M", "7b-instruct-q3_K_L", "7b-instruct-q4_K_S", "7b-instruct-q4_K_M", "7b-instruct-q5_K_S", "7b-instruct-q5_K_M", "7b-instruct-q6_K", "7b-instruct-fp16", "7b-instruct-v1.1-q4_0", "7b-instruct-v1.1-q4_1", "7b-instruct-v1.1-q5_0", "7b-instruct-v1.1-q5_1", "7b-instruct-v1.1-q8_0", "7b-instruct-v1.1-q2_K", "7b-instruct-v1.1-q3_K_S", "7b-instruct-v1.1-q3_K_M", "7b-instruct-v1.1-q3_K_L", "7b-instruct-v1.1-q4_K_S", "7b-instruct-v1.1-q4_K_M", "7b-instruct-v1.1-q5_K_S", "7b-instruct-v1.1-q5_K_M", "7b-instruct-v1.1-q6_K", "7b-instruct-v1.1-fp16", "2b-code", "2b-v1.1", "2b-code-q4_0", "2b-code-q4_1", "2b-code-q5_0", "2b-code-q5_1", "2b-code-q8_0", "2b-code-q2_K", "2b-code-q3_K_S", "2b-code-q3_K_M", "2b-code-q3_K_L", "2b-code-q4_K_S", "2b-code-q4_K_M", "2b-code-q5_K_S", "2b-code-q5_K_M", "2b-code-q6_K", "2b-code-fp16", "2b-code-v1.1-q4_0", "2b-code-v1.1-q4_1", "2b-code-v1.1-q5_0", "2b-code-v1.1-q5_1", "2b-code-v1.1-q8_0", "2b-code-v1.1-q2_K", "2b-code-v1.1-q3_K_S", "2b-code-v1.1-q3_K_M", "2b-code-v1.1-q3_K_L", "2b-code-v1.1-q4_K_S", "2b-code-v1.1-q4_K_M", "2b-code-v1.1-q5_K_S", "2b-code-v1.1-q5_K_M", "2b-code-v1.1-q6_K", "2b-code-v1.1-fp16"]}, "command-r": {"description": "Command R is a Large Language Model optimized for conversational interaction and long context tasks.", "tags": ["latest", "35b", "v0.1", "35b-v0.1-q4_0", "35b-v0.1-q4_1", "35b-v0.1-q5_1", "35b-v0.1-q8_0", "35b-v0.1-q2_K", "35b-v0.1-q3_K_S", "35b-v0.1-q3_K_M", "35b-v0.1-q3_K_L", "35b-v0.1-q4_K_S", "35b-v0.1-q4_K_M", "35b-v0.1-q5_K_S", "35b-v0.1-q5_K_M", "35b-v0.1-q6_K", "35b-v0.1-fp16"]}, "command-r-plus": {"description": "Command R+ is a powerful, scalable large language model purpose-built to excel at real-world enterprise use cases.", "tags": ["latest", "104b", "104b-q4_0", "104b-q8_0", "104b-q2_K", "104b-fp16"]}, "llava": {"description": "🌋 LLaVA is a novel end-to-end trained large multimodal model that combines a vision encoder and Vicuna for general-purpose visual and language understanding. Updated to version 1.6.", "tags": ["latest", "34b", "13b", "7b", "v1.6", "34b-v1.6", "34b-v1.6-q4_0", "34b-v1.6-q4_1", "34b-v1.6-q5_0", "34b-v1.6-q5_1", "34b-v1.6-q8_0", "34b-v1.6-q2_K", "34b-v1.6-q3_K_S", "34b-v1.6-q3_K_M", "34b-v1.6-q3_K_L", "34b-v1.6-q4_K_S", "34b-v1.6-q4_K_M", "34b-v1.6-q5_K_S", "34b-v1.6-q5_K_M", "34b-v1.6-q6_K", "34b-v1.6-fp16", "13b-v1.6", "13b-v1.5-q4_0", "13b-v1.5-q4_1", "13b-v1.5-q5_0", "13b-v1.5-q5_1", "13b-v1.5-q8_0", "13b-v1.5-q2_K", "13b-v1.5-q3_K_S", "13b-v1.5-q3_K_M", "13b-v1.5-q3_K_L", "13b-v1.5-q4_K_S", "13b-v1.5-q4_K_M", "13b-v1.5-q5_K_S", "13b-v1.5-q5_K_M", "13b-v1.5-q6_K", "13b-v1.5-fp16", "13b-v1.6-vicuna-q4_0", "13b-v1.6-vicuna-q4_1", "13b-v1.6-vicuna-q5_0", "13b-v1.6-vicuna-q5_1", "13b-v1.6-vicuna-q8_0", "13b-v1.6-vicuna-q2_K", "13b-v1.6-vicuna-q3_K_S", "13b-v1.6-vicuna-q3_K_M", "13b-v1.6-vicuna-q3_K_L", "13b-v1.6-vicuna-q4_K_S", "13b-v1.6-vicuna-q4_K_M", "13b-v1.6-vicuna-q5_K_S", "13b-v1.6-vicuna-q5_K_M", "13b-v1.6-vicuna-q6_K", "13b-v1.6-vicuna-fp16", "7b-v1.6", "7b-v1.5-q4_0", "7b-v1.5-q4_1", "7b-v1.5-q5_0", "7b-v1.5-q5_1", "7b-v1.5-q8_0", "7b-v1.5-q2_K", "7b-v1.5-q3_K_S", "7b-v1.5-q3_K_M", "7b-v1.5-q3_K_L", "7b-v1.5-q4_K_S", "7b-v1.5-q4_K_M", "7b-v1.5-q5_K_S", "7b-v1.5-q5_K_M", "7b-v1.5-q6_K", "7b-v1.5-fp16", "7b-v1.6-mistral-q4_0", "7b-v1.6-vicuna-q4_0", "7b-v1.6-mistral-q4_1", "7b-v1.6-vicuna-q4_1", "7b-v1.6-mistral-q5_0", "7b-v1.6-vicuna-q5_0", "7b-v1.6-vicuna-q5_1", "7b-v1.6-mistral-q5_1", "7b-v1.6-mistral-q8_0", "7b-v1.6-vicuna-q8_0", "7b-v1.6-vicuna-q2_K", "7b-v1.6-mistral-q2_K", "7b-v1.6-mistral-q3_K_S", "7b-v1.6-vicuna-q3_K_S", "7b-v1.6-vicuna-q3_K_M", "7b-v1.6-mistral-q3_K_M", "7b-v1.6-vicuna-q3_K_L", "7b-v1.6-mistral-q3_K_L", "7b-v1.6-mistral-q4_K_S", "7b-v1.6-vicuna-q4_K_S", "7b-v1.6-vicuna-q4_K_M", "7b-v1.6-mistral-q4_K_M", "7b-v1.6-vicuna-q5_K_S", "7b-v1.6-mistral-q5_K_S", "7b-v1.6-mistral-q5_K_M", "7b-v1.6-vicuna-q5_K_M", "7b-v1.6-mistral-q6_K", "7b-v1.6-vicuna-q6_K", "7b-v1.6-vicuna-fp16", "7b-v1.6-mistral-fp16"]}, "dbrx": {"description": "DBRX is an open, general-purpose LLM created by Databricks.", "tags": ["latest", "132b", "instruct", "132b-instruct-q4_0", "132b-instruct-q8_0", "132b-instruct-q2_K", "132b-instruct-fp16"]}, "codellama": {"description": "A large language model that can use text prompts to generate and discuss code.", "tags": ["latest", "70b", "34b", "13b", "7b", "code", "instruct", "python", "70b-code", "70b-instruct", "70b-python", "70b-code-q4_0", "70b-code-q4_1", "70b-code-q5_0", "70b-code-q5_1", "70b-code-q8_0", "70b-code-q2_K", "70b-code-q3_K_S", "70b-code-q3_K_M", "70b-code-q3_K_L", "70b-code-q4_K_S", "70b-code-q4_K_M", "70b-code-q5_K_S", "70b-code-q5_K_M", "70b-code-q6_K", "70b-code-fp16", "70b-instruct-q4_0", "70b-instruct-q4_1", "70b-instruct-q5_0", "70b-instruct-q5_1", "70b-instruct-q8_0", "70b-instruct-q2_K", "70b-instruct-q3_K_S", "70b-instruct-q3_K_M", "70b-instruct-q3_K_L", "70b-instruct-q4_K_S", "70b-instruct-q4_K_M", "70b-instruct-q5_K_S", "70b-instruct-q5_K_M", "70b-instruct-q6_K", "70b-instruct-fp16", "70b-python-q4_0", "70b-python-q4_1", "70b-python-q5_0", "70b-python-q5_1", "70b-python-q8_0", "70b-python-q2_K", "70b-python-q3_K_S", "70b-python-q3_K_M", "70b-python-q3_K_L", "70b-python-q4_K_S", "70b-python-q4_K_M", "70b-python-q5_K_S", "70b-python-q5_K_M", "70b-python-q6_K", "70b-python-fp16", "34b-code", "34b-instruct", "34b-python", "34b-code-q4_0", "34b-code-q4_1", "34b-code-q5_0", "34b-code-q5_1", "34b-code-q8_0", "34b-code-q2_K", "34b-code-q3_K_S", "34b-code-q3_K_M", "34b-code-q3_K_L", "34b-code-q4_K_S", "34b-code-q4_K_M", "34b-code-q5_K_S", "34b-code-q5_K_M", "34b-code-q6_K", "34b-instruct-q4_0", "34b-instruct-q4_1", "34b-instruct-q5_0", "34b-instruct-q5_1", "34b-instruct-q8_0", "34b-instruct-q2_K", "34b-instruct-q3_K_S", "34b-instruct-q3_K_M", "34b-instruct-q3_K_L", "34b-instruct-q4_K_S", "34b-instruct-q4_K_M", "34b-instruct-q5_K_S", "34b-instruct-q5_K_M", "34b-instruct-q6_K", "34b-instruct-fp16", "34b-python-q4_0", "34b-python-q4_1", "34b-python-q5_0", "34b-python-q5_1", "34b-python-q8_0", "34b-python-q2_K", "34b-python-q3_K_S", "34b-python-q3_K_M", "34b-python-q3_K_L", "34b-python-q4_K_S", "34b-python-q4_K_M", "34b-python-q5_K_S", "34b-python-q5_K_M", "34b-python-q6_K", "34b-python-fp16", "13b-code", "13b-instruct", "13b-python", "13b-code-q4_0", "13b-code-q4_1", "13b-code-q5_0", "13b-code-q5_1", "13b-code-q8_0", "13b-code-q2_K", "13b-code-q3_K_S", "13b-code-q3_K_M", "13b-code-q3_K_L", "13b-code-q4_K_S", "13b-code-q4_K_M", "13b-code-q5_K_S", "13b-code-q5_K_M", "13b-code-q6_K", "13b-code-fp16", "13b-instruct-q4_0", "13b-instruct-q4_1", "13b-instruct-q5_0", "13b-instruct-q5_1", "13b-instruct-q8_0", "13b-instruct-q2_K", "13b-instruct-q3_K_S", "13b-instruct-q3_K_M", "13b-instruct-q3_K_L", "13b-instruct-q4_K_S", "13b-instruct-q4_K_M", "13b-instruct-q5_K_S", "13b-instruct-q5_K_M", "13b-instruct-q6_K", "13b-instruct-fp16", "13b-python-q4_0", "13b-python-q4_1", "13b-python-q5_0", "13b-python-q5_1", "13b-python-q8_0", "13b-python-q2_K", "13b-python-q3_K_S", "13b-python-q3_K_M", "13b-python-q3_K_L", "13b-python-q4_K_S", "13b-python-q4_K_M", "13b-python-q5_K_S", "13b-python-q5_K_M", "13b-python-q6_K", "13b-python-fp16", "7b-code", "7b-instruct", "7b-python", "7b-code-q4_0", "7b-code-q4_1", "7b-code-q5_0", "7b-code-q5_1", "7b-code-q8_0", "7b-code-q2_K", "7b-code-q3_K_S", "7b-code-q3_K_M", "7b-code-q3_K_L", "7b-code-q4_K_S", "7b-code-q4_K_M", "7b-code-q5_K_S", "7b-code-q5_K_M", "7b-code-q6_K", "7b-code-fp16", "7b-instruct-q4_0", "7b-instruct-q4_1", "7b-instruct-q5_0", "7b-instruct-q5_1", "7b-instruct-q8_0", "7b-instruct-q2_K", "7b-instruct-q3_K_S", "7b-instruct-q3_K_M", "7b-instruct-q3_K_L", "7b-instruct-q4_K_S", "7b-instruct-q4_K_M", "7b-instruct-q5_K_S", "7b-instruct-q5_K_M", "7b-instruct-q6_K", "7b-instruct-fp16", "7b-python-q4_0", "7b-python-q4_1", "7b-python-q5_0", "7b-python-q5_1", "7b-python-q8_0", "7b-python-q2_K", "7b-python-q3_K_S", "7b-python-q3_K_M", "7b-python-q3_K_L", "7b-python-q4_K_S", "7b-python-q4_K_M", "7b-python-q5_K_S", "7b-python-q5_K_M", "7b-python-q6_K", "7b-python-fp16"]}, "qwen": {"description": "Qwen 1.5 is a series of large language models by Alibaba Cloud spanning from 0.5B to 110B parameters", "tags": ["latest", "110b", "72b", "32b", "14b", "7b", "4b", "1.8b", "0.5b", "110b-chat", "110b-chat-v1.5-q4_0", "110b-chat-v1.5-q4_1", "110b-chat-v1.5-q5_0", "110b-chat-v1.5-q5_1", "110b-chat-v1.5-q8_0", "110b-chat-v1.5-q2_K", "110b-chat-v1.5-q3_K_S", "110b-chat-v1.5-q3_K_M", "110b-chat-v1.5-q3_K_L", "110b-chat-v1.5-q4_K_S", "110b-chat-v1.5-q4_K_M", "110b-chat-v1.5-q5_K_S", "110b-chat-v1.5-q5_K_M", "110b-chat-v1.5-q6_K", "110b-chat-v1.5-fp16", "110b-text-v1.5-q4_0", "110b-text-v1.5-q4_1", "110b-text-v1.5-q5_0", "110b-text-v1.5-q5_1", "110b-text-v1.5-q8_0", "110b-text-v1.5-q2_K", "110b-text-v1.5-q3_K_S", "110b-text-v1.5-q3_K_M", "110b-text-v1.5-q3_K_L", "110b-text-v1.5-q4_K_S", "110b-text-v1.5-q4_K_M", "110b-text-v1.5-q5_K_S", "110b-text-v1.5-q5_K_M", "110b-text-v1.5-q6_K", "110b-text-v1.5-fp16", "72b-chat", "72b-text", "72b-chat-q4_0", "72b-chat-q4_1", "72b-chat-q5_0", "72b-chat-q5_1", "72b-chat-q8_0", "72b-chat-q2_K", "72b-chat-q3_K_S", "72b-chat-q3_K_M", "72b-chat-q3_K_L", "72b-chat-q4_K_S", "72b-chat-q4_K_M", "72b-chat-q5_K_S", "72b-chat-q5_K_M", "72b-chat-q6_K", "72b-chat-fp16", "72b-text-q4_0", "72b-text-q4_1", "72b-text-q5_0", "72b-text-q5_1", "72b-text-q8_0", "72b-text-q2_K", "72b-text-q3_K_S", "72b-text-q3_K_M", "72b-text-q3_K_L", "72b-text-q4_K_S", "72b-text-q4_K_M", "72b-text-q5_K_S", "72b-text-q5_K_M", "72b-text-q6_K", "72b-text-fp16", "72b-chat-v1.5-q4_0", "72b-chat-v1.5-q4_1", "72b-chat-v1.5-q5_0", "72b-chat-v1.5-q5_1", "72b-chat-v1.5-q8_0", "72b-chat-v1.5-q2_K", "72b-chat-v1.5-q3_K_S", "72b-chat-v1.5-q3_K_M", "72b-chat-v1.5-q3_K_L", "72b-chat-v1.5-q4_K_S", "72b-chat-v1.5-q4_K_M", "72b-chat-v1.5-q5_K_S", "72b-chat-v1.5-q5_K_M", "72b-chat-v1.5-q6_K", "72b-chat-v1.5-fp16", "72b-text-v1.5-q4_0", "72b-text-v1.5-q4_1", "72b-text-v1.5-q5_0", "72b-text-v1.5-q5_1", "72b-text-v1.5-q8_0", "72b-text-v1.5-q2_K", "72b-text-v1.5-q3_K_S", "72b-text-v1.5-q3_K_M", "72b-text-v1.5-q3_K_L", "72b-text-v1.5-q4_K_S", "72b-text-v1.5-q4_K_M", "72b-text-v1.5-q5_K_S", "72b-text-v1.5-q5_K_M", "72b-text-v1.5-q6_K", "72b-text-v1.5-fp16", "32b-chat", "32b-text", "32b-chat-v1.5-q4_0", "32b-chat-v1.5-q4_1", "32b-chat-v1.5-q5_0", "32b-chat-v1.5-q5_1", "32b-chat-v1.5-q8_0", "32b-chat-v1.5-q2_K", "32b-chat-v1.5-q3_K_S", "32b-chat-v1.5-q3_K_M", "32b-chat-v1.5-q3_K_L", "32b-chat-v1.5-q4_K_S", "32b-chat-v1.5-q4_K_M", "32b-chat-v1.5-q5_K_S", "32b-chat-v1.5-q5_K_M", "32b-chat-v1.5-q6_K", "32b-chat-v1.5-fp16", "32b-text-v1.5-q4_0", "32b-text-v1.5-q4_1", "32b-text-v1.5-q5_0", "32b-text-v1.5-q5_1", "32b-text-v1.5-q8_0", "32b-text-v1.5-q2_K", "32b-text-v1.5-q3_K_S", "32b-text-v1.5-q3_K_M", "32b-text-v1.5-q3_K_L", "32b-text-v1.5-q4_K_S", "14b-chat", "14b-text", "14b-chat-q4_0", "14b-chat-q4_1", "14b-chat-q5_0", "14b-chat-q5_1", "14b-chat-q8_0", "14b-chat-q2_K", "14b-chat-q3_K_S", "14b-chat-q3_K_M", "14b-chat-q3_K_L", "14b-chat-q4_K_S", "14b-chat-q4_K_M", "14b-chat-q5_K_S", "14b-chat-q5_K_M", "14b-chat-q6_K", "14b-chat-fp16", "14b-text-q4_0", "14b-text-q4_1", "14b-text-q5_0", "14b-text-q5_1", "14b-text-q8_0", "14b-text-q2_K", "14b-text-q3_K_S", "14b-text-q3_K_M", "14b-text-q3_K_L", "14b-text-q4_K_S", "14b-text-q4_K_M", "14b-text-q5_K_S", "14b-text-q5_K_M", "14b-text-q6_K", "14b-text-fp16", "14b-chat-v1.5-q4_0", "14b-chat-v1.5-q4_1", "14b-chat-v1.5-q5_0", "14b-chat-v1.5-q5_1", "14b-chat-v1.5-q8_0", "14b-chat-v1.5-q2_K", "14b-chat-v1.5-q3_K_S", "14b-chat-v1.5-q3_K_M", "14b-chat-v1.5-q3_K_L", "14b-chat-v1.5-q4_K_S", "14b-chat-v1.5-q4_K_M", "14b-chat-v1.5-q5_K_S", "14b-chat-v1.5-q5_K_M", "14b-chat-v1.5-q6_K", "14b-chat-v1.5-fp16", "14b-text-v1.5-q4_0", "14b-text-v1.5-q4_1", "14b-text-v1.5-q5_0", "14b-text-v1.5-q5_1", "14b-text-v1.5-q8_0", "14b-text-v1.5-q2_K", "14b-text-v1.5-q3_K_S", "14b-text-v1.5-q3_K_M", "14b-text-v1.5-q3_K_L", "14b-text-v1.5-q4_K_S", "14b-text-v1.5-q4_K_M", "14b-text-v1.5-q5_K_S", "14b-text-v1.5-q5_K_M", "14b-text-v1.5-q6_K", "14b-text-v1.5-fp16", "7b-chat", "7b-text", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16", "7b-chat-q4_0", "7b-chat-q4_1", "7b-chat-q5_0", "7b-chat-q5_1", "7b-chat-q8_0", "7b-chat-q2_K", "7b-chat-q3_K_S", "7b-chat-q3_K_M", "7b-chat-q3_K_L", "7b-chat-q4_K_S", "7b-chat-q4_K_M", "7b-chat-q5_K_S", "7b-chat-q5_K_M", "7b-chat-q6_K", "7b-chat-fp16", "7b-chat-v1.5-q4_0", "7b-chat-v1.5-q4_1", "7b-chat-v1.5-q5_0", "7b-chat-v1.5-q5_1", "7b-chat-v1.5-q8_0", "7b-chat-v1.5-q2_K", "7b-chat-v1.5-q3_K_S", "7b-chat-v1.5-q3_K_M", "7b-chat-v1.5-q3_K_L", "7b-chat-v1.5-q4_K_S", "7b-chat-v1.5-q4_K_M", "7b-chat-v1.5-q5_K_S", "7b-chat-v1.5-q5_K_M", "7b-chat-v1.5-q6_K", "7b-chat-v1.5-fp16", "7b-text-v1.5-q4_0", "7b-text-v1.5-q4_1", "7b-text-v1.5-q5_0", "7b-text-v1.5-q5_1", "7b-text-v1.5-q8_0", "7b-text-v1.5-q2_K", "7b-text-v1.5-q3_K_S", "7b-text-v1.5-q3_K_M", "7b-text-v1.5-q3_K_L", "7b-text-v1.5-q4_K_S", "7b-text-v1.5-q4_K_M", "7b-text-v1.5-q5_K_S", "7b-text-v1.5-q5_K_M", "7b-text-v1.5-q6_K", "7b-text-v1.5-fp16", "4b-chat", "4b-text", "4b-chat-v1.5-q4_0", "4b-chat-v1.5-q4_1", "4b-chat-v1.5-q5_0", "4b-chat-v1.5-q5_1", "4b-chat-v1.5-q8_0", "4b-chat-v1.5-q2_K", "4b-chat-v1.5-q3_K_S", "4b-chat-v1.5-q3_K_M", "4b-chat-v1.5-q3_K_L", "4b-chat-v1.5-q4_K_S", "4b-chat-v1.5-q4_K_M", "4b-chat-v1.5-q5_K_S", "4b-chat-v1.5-q5_K_M", "4b-chat-v1.5-q6_K", "4b-chat-v1.5-fp16", "4b-text-v1.5-q4_0", "4b-text-v1.5-q4_1", "4b-text-v1.5-q5_0", "4b-text-v1.5-q5_1", "4b-text-v1.5-q8_0", "4b-text-v1.5-q2_K", "4b-text-v1.5-q3_K_S", "4b-text-v1.5-q3_K_M", "4b-text-v1.5-q3_K_L", "4b-text-v1.5-q4_K_S", "4b-text-v1.5-q4_K_M", "4b-text-v1.5-q5_K_S", "4b-text-v1.5-q5_K_M", "4b-text-v1.5-q6_K", "4b-text-v1.5-fp16", "1.8b-chat", "1.8b-text", "1.8b-chat-q4_0", "1.8b-chat-q4_1", "1.8b-chat-q5_0", "1.8b-chat-q5_1", "1.8b-chat-q8_0", "1.8b-chat-q2_K", "1.8b-chat-q3_K_S", "1.8b-chat-q3_K_M", "1.8b-chat-q3_K_L", "1.8b-chat-q4_K_S", "1.8b-chat-q4_K_M", "1.8b-chat-q5_K_S", "1.8b-chat-q5_K_M", "1.8b-chat-q6_K", "1.8b-chat-fp16", "1.8b-text-q4_0", "1.8b-text-q4_1", "1.8b-text-q5_0", "1.8b-text-q5_1", "1.8b-text-q8_0", "1.8b-text-q2_K", "1.8b-text-q3_K_S", "1.8b-text-q3_K_M", "1.8b-text-q3_K_L", "1.8b-text-q4_K_S", "1.8b-text-q4_K_M", "1.8b-text-q5_K_S", "1.8b-text-q5_K_M", "1.8b-text-q6_K", "1.8b-text-fp16", "1.8b-chat-v1.5-q4_0", "1.8b-chat-v1.5-q4_1", "1.8b-chat-v1.5-q5_0", "1.8b-chat-v1.5-q5_1", "1.8b-chat-v1.5-q8_0", "1.8b-chat-v1.5-q2_K", "1.8b-chat-v1.5-q3_K_S", "1.8b-chat-v1.5-q3_K_M", "1.8b-chat-v1.5-q3_K_L", "1.8b-chat-v1.5-q4_K_S", "1.8b-chat-v1.5-q4_K_M", "1.8b-chat-v1.5-q5_K_S", "1.8b-chat-v1.5-q5_K_M", "1.8b-chat-v1.5-q6_K", "1.8b-chat-v1.5-fp16", "1.8b-text-v1.5-q4_0", "1.8b-text-v1.5-q4_1", "1.8b-text-v1.5-q5_0", "1.8b-text-v1.5-q5_1", "1.8b-text-v1.5-q8_0", "1.8b-text-v1.5-q2_K", "1.8b-text-v1.5-q3_K_S", "1.8b-text-v1.5-q3_K_M", "1.8b-text-v1.5-q3_K_L", "1.8b-text-v1.5-q4_K_S", "1.8b-text-v1.5-q4_K_M", "1.8b-text-v1.5-q5_K_S", "1.8b-text-v1.5-q5_K_M", "1.8b-text-v1.5-q6_K", "1.8b-text-v1.5-fp16", "0.5b-chat", "0.5b-text", "0.5b-chat-v1.5-q4_0", "0.5b-chat-v1.5-q4_1", "0.5b-chat-v1.5-q5_0", "0.5b-chat-v1.5-q5_1", "0.5b-chat-v1.5-q8_0", "0.5b-chat-v1.5-q2_K", "0.5b-chat-v1.5-q3_K_S", "0.5b-chat-v1.5-q3_K_M", "0.5b-chat-v1.5-q3_K_L", "0.5b-chat-v1.5-q4_K_S", "0.5b-chat-v1.5-q4_K_M", "0.5b-chat-v1.5-q5_K_S", "0.5b-chat-v1.5-q5_K_M", "0.5b-chat-v1.5-q6_K", "0.5b-chat-v1.5-fp16", "0.5b-text-v1.5-q4_0", "0.5b-text-v1.5-q4_1", "0.5b-text-v1.5-q5_0", "0.5b-text-v1.5-q5_1", "0.5b-text-v1.5-q8_0", "0.5b-text-v1.5-q2_K", "0.5b-text-v1.5-q3_K_S", "0.5b-text-v1.5-q3_K_M", "0.5b-text-v1.5-q3_K_L", "0.5b-text-v1.5-q4_K_S", "0.5b-text-v1.5-q4_K_M", "0.5b-text-v1.5-q5_K_S", "0.5b-text-v1.5-q5_K_M", "0.5b-text-v1.5-q6_K", "0.5b-text-v1.5-fp16"]}, "dolphin-mixtral": {"description": "Uncensored, 8x7b and 8x22b fine-tuned models based on the Mixtral mixture of experts models that excels at coding tasks. Created by Eric Hartford.", "tags": ["latest", "8x22b", "8x7b", "v2.5", "v2.6", "v2.6.1", "v2.7", "8x7b-v2.5", "8x7b-v2.6", "8x7b-v2.6.1", "8x7b-v2.7", "8x22b-v2.9", "8x7b-v2.5-q4_0", "8x7b-v2.5-q4_1", "8x7b-v2.5-q5_0", "8x7b-v2.5-q5_1", "8x7b-v2.5-q8_0", "8x7b-v2.5-q2_K", "8x7b-v2.5-q3_K_S", "8x7b-v2.5-q3_K_M", "8x7b-v2.5-q3_K_L", "8x7b-v2.5-q4_K_S", "8x7b-v2.5-q4_K_M", "8x7b-v2.5-q5_K_S", "8x7b-v2.5-q5_K_M", "8x7b-v2.5-q6_K", "8x7b-v2.5-fp16", "8x7b-v2.6-q4_0", "8x7b-v2.6-q4_1", "8x7b-v2.6-q5_0", "8x7b-v2.6-q5_1", "8x7b-v2.6-q8_0", "8x7b-v2.6-q2_K", "8x7b-v2.6-q3_K_S", "8x7b-v2.6-q3_K_M", "8x7b-v2.6-q3_K_L", "8x7b-v2.6-q4_K_S", "8x7b-v2.6-q4_K_M", "8x7b-v2.6-q5_K_S", "8x7b-v2.6-q5_K_M", "8x7b-v2.6-q6_K", "8x7b-v2.6-fp16", "8x7b-v2.6.1-q4_0", "8x7b-v2.6.1-q4_1", "8x7b-v2.6.1-q5_0", "8x7b-v2.6.1-q5_1", "8x7b-v2.6.1-q8_0", "8x7b-v2.6.1-q2_K", "8x7b-v2.6.1-q3_K_S", "8x7b-v2.6.1-q3_K_M", "8x7b-v2.6.1-q3_K_L", "8x7b-v2.6.1-q4_K_S", "8x7b-v2.6.1-q4_K_M", "8x7b-v2.6.1-q5_K_S", "8x7b-v2.6.1-q5_K_M", "8x7b-v2.6.1-q6_K", "8x7b-v2.6.1-fp16", "8x7b-v2.7-q4_0", "8x7b-v2.7-q4_1", "8x7b-v2.7-q5_0", "8x7b-v2.7-q5_1", "8x7b-v2.7-q8_0", "8x7b-v2.7-q2_K", "8x7b-v2.7-q3_K_S", "8x7b-v2.7-q3_K_M", "8x7b-v2.7-q3_K_L", "8x7b-v2.7-q4_K_S", "8x7b-v2.7-q4_K_M", "8x7b-v2.7-q5_K_S", "8x7b-v2.7-q5_K_M", "8x7b-v2.7-q6_K", "8x7b-v2.7-fp16", "8x22b-v2.9-q4_0", "8x22b-v2.9-q4_1", "8x22b-v2.9-q5_0", "8x22b-v2.9-q5_1", "8x22b-v2.9-q8_0", "8x22b-v2.9-q2_K", "8x22b-v2.9-q3_K_S", "8x22b-v2.9-q3_K_M", "8x22b-v2.9-q3_K_L", "8x22b-v2.9-q4_K_S", "8x22b-v2.9-q4_K_M", "8x22b-v2.9-q5_K_S", "8x22b-v2.9-q5_K_M", "8x22b-v2.9-q6_K", "8x22b-v2.9-fp16"]}, "llama2-uncensored": {"description": "Uncensored Llama 2 model by George Sung and Jarrad Hope.", "tags": ["latest", "70b", "7b", "70b-chat", "70b-chat-q4_0", "70b-chat-q4_1", "70b-chat-q5_0", "70b-chat-q5_1", "70b-chat-q8_0", "70b-chat-q2_K", "70b-chat-q3_K_S", "70b-chat-q3_K_M", "70b-chat-q3_K_L", "70b-chat-q4_K_S", "70b-chat-q4_K_M", "70b-chat-q5_K_S", "70b-chat-q5_K_M", "70b-chat-q6_K", "7b-chat", "7b-chat-q4_0", "7b-chat-q4_1", "7b-chat-q5_0", "7b-chat-q5_1", "7b-chat-q8_0", "7b-chat-q2_K", "7b-chat-q3_K_S", "7b-chat-q3_K_M", "7b-chat-q3_K_L", "7b-chat-q4_K_S", "7b-chat-q4_K_M", "7b-chat-q5_K_S", "7b-chat-q5_K_M", "7b-chat-q6_K", "7b-chat-fp16"]}, "deepseek-coder": {"description": "DeepSeek Coder is a capable coding model trained on two trillion code and natural language tokens.", "tags": ["latest", "33b", "6.7b", "1.3b", "base", "instruct", "33b-base", "33b-instruct", "33b-base-q4_0", "33b-base-q4_1", "33b-base-q5_0", "33b-base-q5_1", "33b-base-q8_0", "33b-base-q2_K", "33b-base-q3_K_S", "33b-base-q3_K_M", "33b-base-q3_K_L", "33b-base-q4_K_S", "33b-base-q4_K_M", "33b-base-q5_K_S", "33b-base-q5_K_M", "33b-base-q6_K", "33b-base-fp16", "33b-instruct-q4_0", "33b-instruct-q4_1", "33b-instruct-q5_0", "33b-instruct-q5_1", "33b-instruct-q8_0", "33b-instruct-q2_K", "33b-instruct-q3_K_S", "33b-instruct-q3_K_M", "33b-instruct-q3_K_L", "33b-instruct-q4_K_S", "33b-instruct-q4_K_M", "33b-instruct-q5_K_S", "33b-instruct-q5_K_M", "33b-instruct-q6_K", "33b-instruct-fp16", "6.7b-base", "6.7b-instruct", "6.7b-base-q4_0", "6.7b-base-q4_1", "6.7b-base-q5_0", "6.7b-base-q5_1", "6.7b-base-q8_0", "6.7b-base-q2_K", "6.7b-base-q3_K_S", "6.7b-base-q3_K_M", "6.7b-base-q3_K_L", "6.7b-base-q4_K_S", "6.7b-base-q4_K_M", "6.7b-base-q5_K_S", "6.7b-base-q5_K_M", "6.7b-base-q6_K", "6.7b-base-fp16", "6.7b-instruct-q4_0", "6.7b-instruct-q4_1", "6.7b-instruct-q5_0", "6.7b-instruct-q5_1", "6.7b-instruct-q8_0", "6.7b-instruct-q2_K", "6.7b-instruct-q3_K_S", "6.7b-instruct-q3_K_M", "6.7b-instruct-q3_K_L", "6.7b-instruct-q4_K_S", "6.7b-instruct-q4_K_M", "6.7b-instruct-q5_K_S", "6.7b-instruct-q5_K_M", "6.7b-instruct-q6_K", "6.7b-instruct-fp16", "1.3b-base", "1.3b-instruct", "1.3b-base-q4_0", "1.3b-base-q4_1", "1.3b-base-q5_0", "1.3b-base-q5_1", "1.3b-base-q8_0", "1.3b-base-q2_K", "1.3b-base-q3_K_S", "1.3b-base-q3_K_M", "1.3b-base-q3_K_L", "1.3b-base-q4_K_S", "1.3b-base-q4_K_M", "1.3b-base-q5_K_S", "1.3b-base-q5_K_M", "1.3b-base-q6_K", "1.3b-base-fp16", "1.3b-instruct-q4_0", "1.3b-instruct-q4_1", "1.3b-instruct-q5_0", "1.3b-instruct-q5_1", "1.3b-instruct-q8_0", "1.3b-instruct-q2_K", "1.3b-instruct-q3_K_S", "1.3b-instruct-q3_K_M", "1.3b-instruct-q3_K_L", "1.3b-instruct-q4_K_S", "1.3b-instruct-q4_K_M", "1.3b-instruct-q5_K_S", "1.3b-instruct-q5_K_M", "1.3b-instruct-q6_K", "1.3b-instruct-fp16"]}, "mistral-openorca": {"description": "Mistral OpenOrca is a 7 billion parameter model, fine-tuned on top of the Mistral 7B model using the OpenOrca dataset.", "tags": ["latest", "7b", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "nomic-embed-text": {"description": "A high-performing open embedding model with a large token context window.", "tags": ["latest", "v1.5", "137m-v1.5-fp16"]}, "dolphin-mistral": {"description": "The uncensored Dolphin model based on Mistral that excels at coding tasks. Updated to version 2.8.", "tags": ["latest", "7b", "v2", "v2.1", "v2.2", "v2.2.1", "v2.6", "v2.8", "7b-v2", "7b-v2.1", "7b-v2.2", "7b-v2.2.1", "7b-v2.6", "7b-v2.8", "7b-v2-q4_0", "7b-v2-q4_1", "7b-v2-q5_0", "7b-v2-q5_1", "7b-v2-q8_0", "7b-v2-q2_K", "7b-v2-q3_K_S", "7b-v2-q3_K_M", "7b-v2-q3_K_L", "7b-v2-q4_K_S", "7b-v2-q4_K_M", "7b-v2-q5_K_S", "7b-v2-q5_K_M", "7b-v2-q6_K", "7b-v2-fp16", "7b-v2.1-q4_0", "7b-v2.1-q4_1", "7b-v2.1-q5_0", "7b-v2.1-q5_1", "7b-v2.1-q8_0", "7b-v2.1-q2_K", "7b-v2.1-q3_K_S", "7b-v2.1-q3_K_M", "7b-v2.1-q3_K_L", "7b-v2.1-q4_K_S", "7b-v2.1-q4_K_M", "7b-v2.1-q5_K_S", "7b-v2.1-q5_K_M", "7b-v2.1-q6_K", "7b-v2.1-fp16", "7b-v2.2-q4_0", "7b-v2.2-q4_1", "7b-v2.2-q5_0", "7b-v2.2-q5_1", "7b-v2.2-q8_0", "7b-v2.2-q2_K", "7b-v2.2-q3_K_S", "7b-v2.2-q3_K_M", "7b-v2.2-q3_K_L", "7b-v2.2-q4_K_S", "7b-v2.2-q4_K_M", "7b-v2.2-q5_K_S", "7b-v2.2-q5_K_M", "7b-v2.2-q6_K", "7b-v2.2-fp16", "7b-v2.2.1-q4_0", "7b-v2.2.1-q4_1", "7b-v2.2.1-q5_0", "7b-v2.2.1-q5_1", "7b-v2.2.1-q8_0", "7b-v2.2.1-q2_K", "7b-v2.2.1-q3_K_S", "7b-v2.2.1-q3_K_M", "7b-v2.2.1-q3_K_L", "7b-v2.2.1-q4_K_S", "7b-v2.2.1-q4_K_M", "7b-v2.2.1-q5_K_S", "7b-v2.2.1-q5_K_M", "7b-v2.2.1-q6_K", "7b-v2.2.1-fp16", "7b-v2.6-q4_0", "7b-v2.6-q4_1", "7b-v2.6-q5_0", "7b-v2.6-q5_1", "7b-v2.6-q8_0", "7b-v2.6-q2_K", "7b-v2.6-q3_K_S", "7b-v2.6-q3_K_M", "7b-v2.6-q3_K_L", "7b-v2.6-q4_K_S", "7b-v2.6-q4_K_M", "7b-v2.6-q5_K_S", "7b-v2.6-q5_K_M", "7b-v2.6-q6_K", "7b-v2.6-fp16", "7b-v2.8-q4_0", "7b-v2.8-q4_1", "7b-v2.8-q5_0", "7b-v2.8-q5_1", "7b-v2.8-q8_0", "7b-v2.8-q2_K", "7b-v2.8-q3_K_S", "7b-v2.8-q3_K_M", "7b-v2.8-q3_K_L", "7b-v2.8-q4_K_S", "7b-v2.8-q4_K_M", "7b-v2.8-q5_K_S", "7b-v2.8-q5_K_M", "7b-v2.8-q6_K", "7b-v2.8-fp16", "7b-v2.6-dpo-laser", "7b-v2.6-dpo-laser-q4_0", "7b-v2.6-dpo-laser-q4_1", "7b-v2.6-dpo-laser-q5_0", "7b-v2.6-dpo-laser-q5_1", "7b-v2.6-dpo-laser-q8_0", "7b-v2.6-dpo-laser-q2_K", "7b-v2.6-dpo-laser-q3_K_S", "7b-v2.6-dpo-laser-q3_K_M", "7b-v2.6-dpo-laser-q3_K_L", "7b-v2.6-dpo-laser-q4_K_S", "7b-v2.6-dpo-laser-q4_K_M", "7b-v2.6-dpo-laser-q5_K_S", "7b-v2.6-dpo-laser-q5_K_M", "7b-v2.6-dpo-laser-q6_K", "7b-v2.6-dpo-laser-fp16"]}, "phi": {"description": "Phi-2: a 2.7B language model by Microsoft Research that demonstrates outstanding reasoning and language understanding capabilities.", "tags": ["latest", "2.7b", "chat", "2.7b-chat-v2-q4_0", "2.7b-chat-v2-q4_1", "2.7b-chat-v2-q5_0", "2.7b-chat-v2-q5_1", "2.7b-chat-v2-q8_0", "2.7b-chat-v2-q2_K", "2.7b-chat-v2-q3_K_S", "2.7b-chat-v2-q3_K_M", "2.7b-chat-v2-q3_K_L", "2.7b-chat-v2-q4_K_S", "2.7b-chat-v2-q4_K_M", "2.7b-chat-v2-q5_K_S", "2.7b-chat-v2-q5_K_M", "2.7b-chat-v2-q6_K", "2.7b-chat-v2-fp16"]}, "orca-mini": {"description": "A general-purpose model ranging from 3 billion parameters to 70 billion, suitable for entry-level hardware.", "tags": ["latest", "70b", "13b", "7b", "3b", "70b-v3", "70b-v3-q4_0", "70b-v3-q4_1", "70b-v3-q5_0", "70b-v3-q5_1", "70b-v3-q8_0", "70b-v3-q2_K", "70b-v3-q3_K_S", "70b-v3-q3_K_M", "70b-v3-q3_K_L", "70b-v3-q4_K_S", "70b-v3-q4_K_M", "70b-v3-q5_K_S", "70b-v3-q5_K_M", "70b-v3-q6_K", "70b-v3-fp16", "13b-v3", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16", "13b-v2-q4_0", "13b-v2-q4_1", "13b-v2-q5_0", "13b-v2-q5_1", "13b-v2-q8_0", "13b-v2-q2_K", "13b-v2-q3_K_S", "13b-v2-q3_K_M", "13b-v2-q3_K_L", "13b-v2-q4_K_S", "13b-v2-q4_K_M", "13b-v2-q5_K_S", "13b-v2-q5_K_M", "13b-v2-q6_K", "13b-v2-fp16", "13b-v3-q4_0", "13b-v3-q4_1", "13b-v3-q5_0", "13b-v3-q5_1", "13b-v3-q8_0", "13b-v3-q2_K", "13b-v3-q3_K_S", "13b-v3-q3_K_M", "13b-v3-q3_K_L", "13b-v3-q4_K_S", "13b-v3-q4_K_M", "13b-v3-q5_K_S", "13b-v3-q5_K_M", "13b-v3-q6_K", "13b-v3-fp16", "7b-v3", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16", "7b-v2-q4_0", "7b-v2-q4_1", "7b-v2-q5_0", "7b-v2-q5_1", "7b-v2-q8_0", "7b-v2-q2_K", "7b-v2-q3_K_S", "7b-v2-q3_K_M", "7b-v2-q3_K_L", "7b-v2-q4_K_S", "7b-v2-q4_K_M", "7b-v2-q5_K_S", "7b-v2-q5_K_M", "7b-v2-q6_K", "7b-v2-fp16", "7b-v3-q4_0", "7b-v3-q4_1", "7b-v3-q5_0", "7b-v3-q5_1", "7b-v3-q8_0", "7b-v3-q2_K", "7b-v3-q3_K_S", "7b-v3-q3_K_M", "7b-v3-q3_K_L", "7b-v3-q4_K_S", "7b-v3-q4_K_M", "7b-v3-q5_K_S", "7b-v3-q5_K_M", "7b-v3-q6_K", "7b-v3-fp16", "3b-q4_0", "3b-q4_1", "3b-q5_0", "3b-q5_1", "3b-q8_0", "3b-fp16"]}, "nous-hermes2": {"description": "The powerful family of models by Nous Research that excels at scientific discussion and coding tasks.", "tags": ["latest", "34b", "10.7b", "34b-yi-q4_0", "34b-yi-q4_1", "34b-yi-q5_0", "34b-yi-q5_1", "34b-yi-q8_0", "34b-yi-q2_K", "34b-yi-q3_K_S", "34b-yi-q3_K_M", "34b-yi-q3_K_L", "34b-yi-q4_K_S", "34b-yi-q4_K_M", "34b-yi-q5_K_S", "34b-yi-q5_K_M", "34b-yi-q6_K", "34b-yi-fp16", "10.7b-solar-q4_0", "10.7b-solar-q4_1", "10.7b-solar-q5_0", "10.7b-solar-q5_1", "10.7b-solar-q8_0", "10.7b-solar-q2_K", "10.7b-solar-q3_K_S", "10.7b-solar-q3_K_M", "10.7b-solar-q3_K_L", "10.7b-solar-q4_K_S", "10.7b-solar-q4_K_M", "10.7b-solar-q5_K_S", "10.7b-solar-q5_K_M", "10.7b-solar-q6_K", "10.7b-solar-fp16"]}, "zephyr": {"description": "Zephyr is a series of fine-tuned versions of the Mistral and Mixtral models that are trained to act as helpful assistants.", "tags": ["latest", "141b", "7b", "141b-v0.1", "141b-v0.1-q4_0", "141b-v0.1-q8_0", "141b-v0.1-q2_K", "141b-v0.1-fp16", "7b-alpha", "7b-beta", "7b-alpha-q4_0", "7b-alpha-q4_1", "7b-alpha-q5_0", "7b-alpha-q5_1", "7b-alpha-q8_0", "7b-alpha-q2_K", "7b-alpha-q3_K_S", "7b-alpha-q3_K_M", "7b-alpha-q3_K_L", "7b-alpha-q4_K_S", "7b-alpha-q4_K_M", "7b-alpha-q5_K_S", "7b-alpha-q5_K_M", "7b-alpha-q6_K", "7b-alpha-fp16", "7b-beta-q4_0", "7b-beta-q4_1", "7b-beta-q5_0", "7b-beta-q5_1", "7b-beta-q8_0", "7b-beta-q2_K", "7b-beta-q3_K_S", "7b-beta-q3_K_M", "7b-beta-q3_K_L", "7b-beta-q4_K_S", "7b-beta-q4_K_M", "7b-beta-q5_K_S", "7b-beta-q5_K_M", "7b-beta-q6_K", "7b-beta-fp16"]}, "llama2-chinese": {"description": "Llama 2 based model fine tuned to improve Chinese dialogue ability.", "tags": ["latest", "13b", "7b", "13b-chat", "13b-chat-q4_0", "13b-chat-q4_1", "13b-chat-q5_0", "13b-chat-q5_1", "13b-chat-q8_0", "13b-chat-q2_K", "13b-chat-q3_K_S", "13b-chat-q3_K_M", "13b-chat-q3_K_L", "13b-chat-q4_K_S", "13b-chat-q4_K_M", "13b-chat-q5_K_S", "13b-chat-q5_K_M", "13b-chat-q6_K", "13b-chat-fp16", "7b-chat", "7b-chat-q4_0", "7b-chat-q4_1", "7b-chat-q5_0", "7b-chat-q5_1", "7b-chat-q8_0", "7b-chat-q2_K", "7b-chat-q3_K_S", "7b-chat-q3_K_M", "7b-chat-q3_K_L", "7b-chat-q4_K_S", "7b-chat-q4_K_M", "7b-chat-q5_K_S", "7b-chat-q5_K_M", "7b-chat-q6_K", "7b-chat-fp16"]}, "wizard-vicuna-uncensored": {"description": "Wizard Vicuna Uncensored is a 7B, 13B, and 30B parameter model based on Llama 2 uncensored by Eric Hartford.", "tags": ["latest", "30b", "13b", "7b", "30b-q4_0", "30b-q4_1", "30b-q5_0", "30b-q5_1", "30b-q8_0", "30b-q2_K", "30b-q3_K_S", "30b-q3_K_M", "30b-q3_K_L", "30b-q4_K_S", "30b-q4_K_M", "30b-q5_K_S", "30b-q5_K_M", "30b-q6_K", "30b-fp16", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "starcoder2": {"description": "StarCoder2 is the next generation of transparently trained open code LLMs that comes in three sizes: 3B, 7B and 15B parameters.", "tags": ["latest", "15b", "7b", "3b", "instruct", "15b-instruct", "15b-q4_0", "15b-q4_1", "15b-q5_0", "15b-q5_1", "15b-q8_0", "15b-q2_K", "15b-q3_K_S", "15b-q3_K_M", "15b-q3_K_L", "15b-q4_K_S", "15b-q4_K_M", "15b-q5_K_S", "15b-q5_K_M", "15b-q6_K", "15b-fp16", "15b-instruct-q4_0", "15b-instruct-v0.1-q4_0", "15b-instruct-v0.1-q4_1", "15b-instruct-v0.1-q5_0", "15b-instruct-v0.1-q5_1", "15b-instruct-v0.1-q8_0", "15b-instruct-v0.1-q2_K", "15b-instruct-v0.1-q3_K_S", "15b-instruct-v0.1-q3_K_M", "15b-instruct-v0.1-q3_K_L", "15b-instruct-v0.1-q4_K_S", "15b-instruct-v0.1-q4_K_M", "15b-instruct-v0.1-q5_K_S", "15b-instruct-v0.1-q5_K_M", "15b-instruct-v0.1-q6_K", "15b-instruct-v0.1-fp16", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16", "3b-q4_0", "3b-q4_1", "3b-q5_0", "3b-q5_1", "3b-q8_0", "3b-q2_K", "3b-q3_K_S", "3b-q3_K_M", "3b-q3_K_L", "3b-q4_K_S", "3b-q4_K_M", "3b-q5_K_S", "3b-q5_K_M", "3b-q6_K", "3b-fp16"]}, "vicuna": {"description": "General use chat model based on Llama and Llama 2 with 2K to 16K context sizes.", "tags": ["latest", "33b", "13b", "7b", "33b-q4_0", "33b-q4_1", "33b-q5_0", "33b-q5_1", "33b-q8_0", "33b-q2_K", "33b-q3_K_S", "33b-q3_K_M", "33b-q3_K_L", "33b-q4_K_S", "33b-q4_K_M", "33b-q5_K_S", "33b-q5_K_M", "33b-q6_K", "33b-fp16", "13b-16k", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16", "13b-v1.5-q4_0", "13b-v1.5-q4_1", "13b-v1.5-q5_0", "13b-v1.5-q5_1", "13b-v1.5-q8_0", "13b-v1.5-q2_K", "13b-v1.5-q3_K_S", "13b-v1.5-q3_K_M", "13b-v1.5-q3_K_L", "13b-v1.5-q4_K_S", "13b-v1.5-q4_K_M", "13b-v1.5-q5_K_S", "13b-v1.5-q5_K_M", "13b-v1.5-q6_K", "13b-v1.5-fp16", "13b-v1.5-16k-q4_0", "13b-v1.5-16k-q4_1", "13b-v1.5-16k-q5_0", "13b-v1.5-16k-q5_1", "13b-v1.5-16k-q8_0", "13b-v1.5-16k-q2_K", "13b-v1.5-16k-q3_K_S", "13b-v1.5-16k-q3_K_M", "13b-v1.5-16k-q3_K_L", "13b-v1.5-16k-q4_K_S", "13b-v1.5-16k-q4_K_M", "13b-v1.5-16k-q5_K_S", "13b-v1.5-16k-q5_K_M", "13b-v1.5-16k-q6_K", "13b-v1.5-16k-fp16", "7b-16k", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16", "7b-v1.5-q4_0", "7b-v1.5-q4_1", "7b-v1.5-q5_0", "7b-v1.5-q5_1", "7b-v1.5-q8_0", "7b-v1.5-q2_K", "7b-v1.5-q3_K_S", "7b-v1.5-q3_K_M", "7b-v1.5-q3_K_L", "7b-v1.5-q4_K_S", "7b-v1.5-q4_K_M", "7b-v1.5-q5_K_S", "7b-v1.5-q5_K_M", "7b-v1.5-q6_K", "7b-v1.5-fp16", "7b-v1.5-16k-q4_0", "7b-v1.5-16k-q4_1", "7b-v1.5-16k-q5_0", "7b-v1.5-16k-q5_1", "7b-v1.5-16k-q8_0", "7b-v1.5-16k-q2_K", "7b-v1.5-16k-q3_K_S", "7b-v1.5-16k-q3_K_M", "7b-v1.5-16k-q3_K_L", "7b-v1.5-16k-q4_K_S", "7b-v1.5-16k-q4_K_M", "7b-v1.5-16k-q5_K_S", "7b-v1.5-16k-q5_K_M", "7b-v1.5-16k-q6_K", "7b-v1.5-16k-fp16"]}, "tinyllama": {"description": "The TinyLlama project is an open endeavor to train a compact 1.1B Llama model on 3 trillion tokens.", "tags": ["latest", "1.1b", "chat", "v0.6", "v1", "1.1b-chat", "1.1b-chat-v1-q4_0", "1.1b-chat-v0.6-q4_0", "1.1b-chat-v1-q4_1", "1.1b-chat-v0.6-q4_1", "1.1b-chat-v1-q5_0", "1.1b-chat-v0.6-q5_0", "1.1b-chat-v1-q5_1", "1.1b-chat-v0.6-q5_1", "1.1b-chat-v0.6-q8_0", "1.1b-chat-v1-q8_0", "1.1b-chat-v1-q2_K", "1.1b-chat-v0.6-q2_K", "1.1b-chat-v0.6-q3_K_S", "1.1b-chat-v1-q3_K_S", "1.1b-chat-v0.6-q3_K_M", "1.1b-chat-v1-q3_K_M", "1.1b-chat-v0.6-q3_K_L", "1.1b-chat-v1-q3_K_L", "1.1b-chat-v0.6-q4_K_S", "1.1b-chat-v1-q4_K_S", "1.1b-chat-v1-q4_K_M", "1.1b-chat-v0.6-q4_K_M", "1.1b-chat-v1-q5_K_S", "1.1b-chat-v0.6-q5_K_S", "1.1b-chat-v0.6-q5_K_M", "1.1b-chat-v1-q5_K_M", "1.1b-chat-v0.6-q6_K", "1.1b-chat-v1-q6_K", "1.1b-chat-v0.6-fp16", "1.1b-chat-v1-fp16"]}, "openhermes": {"description": "OpenHermes 2.5 is a 7B model fine-tuned by Teknium on Mistral with fully open datasets.", "tags": ["latest", "v2", "v2.5", "7b-v2", "7b-v2.5", "7b-mistral-v2-q4_0", "7b-mistral-v2.5-q4_0", "7b-mistral-v2-q4_1", "7b-mistral-v2.5-q4_1", "7b-mistral-v2.5-q5_0", "7b-mistral-v2-q5_0", "7b-mistral-v2.5-q5_1", "7b-mistral-v2-q5_1", "7b-mistral-v2.5-q8_0", "7b-mistral-v2-q8_0", "7b-mistral-v2-q2_K", "7b-mistral-v2.5-q2_K", "7b-mistral-v2.5-q3_K_S", "7b-mistral-v2-q3_K_S", "7b-mistral-v2-q3_K_M", "7b-mistral-v2.5-q3_K_M", "7b-mistral-v2.5-q3_K_L", "7b-mistral-v2-q3_K_L", "7b-mistral-v2-q4_K_S", "7b-mistral-v2.5-q4_K_S", "7b-mistral-v2.5-q4_K_M", "7b-mistral-v2-q4_K_M", "7b-mistral-v2.5-q5_K_S", "7b-mistral-v2-q5_K_S", "7b-mistral-v2-q5_K_M", "7b-mistral-v2.5-q5_K_M", "7b-mistral-v2-q6_K", "7b-mistral-v2.5-q6_K", "7b-mistral-v2.5-fp16", "7b-mistral-v2-fp16"]}, "starcoder": {"description": "StarCoder is a code generation model trained on 80+ programming languages.", "tags": ["latest", "15b", "7b", "3b", "1b", "15b-base", "15b-plus", "15b-q4_0", "15b-q4_1", "15b-q5_0", "15b-q5_1", "15b-q8_0", "15b-q2_K", "15b-q3_K_S", "15b-q3_K_M", "15b-q3_K_L", "15b-q4_K_S", "15b-q4_K_M", "15b-q5_K_S", "15b-q5_K_M", "15b-q6_K", "15b-fp16", "15b-base-q4_0", "15b-base-q4_1", "15b-base-q5_0", "15b-base-q5_1", "15b-base-q8_0", "15b-base-q2_K", "15b-base-q3_K_S", "15b-base-q3_K_M", "15b-base-q3_K_L", "15b-base-q4_K_S", "15b-base-q4_K_M", "15b-base-q5_K_S", "15b-base-q5_K_M", "15b-base-q6_K", "15b-base-fp16", "15b-plus-q4_0", "15b-plus-q4_1", "15b-plus-q5_0", "15b-plus-q5_1", "15b-plus-q8_0", "15b-plus-q2_K", "15b-plus-q3_K_S", "15b-plus-q3_K_M", "15b-plus-q3_K_L", "15b-plus-q4_K_S", "15b-plus-q4_K_M", "15b-plus-q5_K_S", "15b-plus-q5_K_M", "15b-plus-q6_K", "15b-plus-fp16", "7b-base", "7b-base-q4_0", "7b-base-q4_1", "7b-base-q5_0", "7b-base-q5_1", "7b-base-q8_0", "7b-base-q2_K", "7b-base-q3_K_S", "7b-base-q3_K_M", "7b-base-q3_K_L", "7b-base-q4_K_S", "7b-base-q4_K_M", "7b-base-q5_K_S", "7b-base-q5_K_M", "7b-base-q6_K", "7b-base-fp16", "3b-base", "3b-base-q4_0", "3b-base-q4_1", "3b-base-q5_0", "3b-base-q5_1", "3b-base-q8_0", "3b-base-q2_K", "3b-base-q3_K_S", "3b-base-q3_K_M", "3b-base-q3_K_L", "3b-base-q4_K_S", "3b-base-q4_K_M", "3b-base-q5_K_S", "3b-base-q5_K_M", "3b-base-q6_K", "3b-base-fp16", "1b-base", "1b-base-q4_0", "1b-base-q4_1", "1b-base-q5_0", "1b-base-q5_1", "1b-base-q8_0", "1b-base-q2_K", "1b-base-q3_K_S", "1b-base-q3_K_M", "1b-base-q3_K_L", "1b-base-q4_K_S", "1b-base-q4_K_M", "1b-base-q5_K_S", "1b-base-q5_K_M", "1b-base-q6_K", "1b-base-fp16"]}, "openchat": {"description": "A family of open-source models trained on a wide variety of data, surpassing ChatGPT on various benchmarks. Updated to version 3.5-0106.", "tags": ["latest", "7b", "7b-v3.5", "7b-v3.5-0106", "7b-v3.5-1210", "7b-v3.5-q4_0", "7b-v3.5-q4_1", "7b-v3.5-q5_0", "7b-v3.5-q5_1", "7b-v3.5-q8_0", "7b-v3.5-q2_K", "7b-v3.5-q3_K_S", "7b-v3.5-q3_K_M", "7b-v3.5-q3_K_L", "7b-v3.5-q4_K_S", "7b-v3.5-q4_K_M", "7b-v3.5-q5_K_S", "7b-v3.5-q5_K_M", "7b-v3.5-q6_K", "7b-v3.5-fp16", "7b-v3.5-0106-q4_0", "7b-v3.5-1210-q4_0", "7b-v3.5-0106-q4_1", "7b-v3.5-1210-q4_1", "7b-v3.5-1210-q5_0", "7b-v3.5-0106-q5_0", "7b-v3.5-0106-q5_1", "7b-v3.5-1210-q5_1", "7b-v3.5-1210-q8_0", "7b-v3.5-0106-q8_0", "7b-v3.5-0106-q2_K", "7b-v3.5-1210-q2_K", "7b-v3.5-1210-q3_K_S", "7b-v3.5-0106-q3_K_S", "7b-v3.5-0106-q3_K_M", "7b-v3.5-1210-q3_K_M", "7b-v3.5-0106-q3_K_L", "7b-v3.5-1210-q3_K_L", "7b-v3.5-0106-q4_K_S", "7b-v3.5-1210-q4_K_S", "7b-v3.5-0106-q4_K_M", "7b-v3.5-1210-q4_K_M", "7b-v3.5-0106-q5_K_S", "7b-v3.5-1210-q5_K_S", "7b-v3.5-1210-q5_K_M", "7b-v3.5-0106-q5_K_M", "7b-v3.5-0106-q6_K", "7b-v3.5-1210-q6_K", "7b-v3.5-0106-fp16", "7b-v3.5-1210-fp16"]}, "yi": {"description": "Yi 1.5 is a high-performing, bilingual language model.", "tags": ["latest", "34b", "9b", "6b", "v1.5", "34b-chat", "34b-v1.5", "34b-q4_0", "34b-q4_1", "34b-q5_0", "34b-q5_1", "34b-q2_K", "34b-q3_K_S", "34b-q3_K_M", "34b-q3_K_L", "34b-q4_K_S", "34b-q4_K_M", "34b-q5_K_S", "34b-q6_K", "34b-chat-q4_0", "34b-chat-q4_1", "34b-chat-q5_0", "34b-chat-q5_1", "34b-chat-q8_0", "34b-chat-q2_K", "34b-chat-q3_K_S", "34b-chat-q3_K_M", "34b-chat-q3_K_L", "34b-chat-q4_K_S", "34b-chat-q4_K_M", "34b-chat-q5_K_S", "34b-chat-q5_K_M", "34b-chat-q6_K", "34b-chat-fp16", "34b-v1.5-q4_0", "34b-v1.5-q4_1", "34b-v1.5-q5_0", "34b-v1.5-q5_1", "34b-v1.5-q8_0", "34b-v1.5-q2_K", "34b-v1.5-q3_K_S", "34b-v1.5-q3_K_M", "34b-v1.5-q3_K_L", "34b-v1.5-q4_K_S", "34b-v1.5-q4_K_M", "34b-v1.5-q5_K_S", "34b-v1.5-q5_K_M", "34b-v1.5-q6_K", "34b-v1.5-fp16", "34b-chat-v1.5-q4_0", "34b-chat-v1.5-q4_1", "34b-chat-v1.5-q5_0", "34b-chat-v1.5-q5_1", "34b-chat-v1.5-q8_0", "34b-chat-v1.5-q2_K", "34b-chat-v1.5-q3_K_S", "34b-chat-v1.5-q3_K_M", "34b-chat-v1.5-q3_K_L", "34b-chat-v1.5-q4_K_S", "34b-chat-v1.5-q4_K_M", "34b-chat-v1.5-q5_K_S", "34b-chat-v1.5-q5_K_M", "34b-chat-v1.5-q6_K", "34b-chat-v1.5-fp16", "9b-chat", "9b-v1.5", "9b-v1.5-q4_0", "9b-v1.5-q4_1", "9b-v1.5-q5_0", "9b-v1.5-q5_1", "9b-v1.5-q8_0", "9b-v1.5-q2_K", "9b-v1.5-q3_K_S", "9b-v1.5-q3_K_M", "9b-v1.5-q3_K_L", "9b-v1.5-q4_K_S", "9b-v1.5-q4_K_M", "9b-v1.5-q5_K_S", "9b-v1.5-q5_K_M", "9b-v1.5-q6_K", "9b-v1.5-fp16", "9b-chat-v1.5-q4_0", "9b-chat-v1.5-q4_1", "9b-chat-v1.5-q5_0", "9b-chat-v1.5-q5_1", "9b-chat-v1.5-q8_0", "9b-chat-v1.5-q2_K", "9b-chat-v1.5-q3_K_S", "9b-chat-v1.5-q3_K_M", "9b-chat-v1.5-q3_K_L", "9b-chat-v1.5-q4_K_S", "9b-chat-v1.5-q4_K_M", "9b-chat-v1.5-q5_K_S", "9b-chat-v1.5-q5_K_M", "9b-chat-v1.5-q6_K", "9b-chat-v1.5-fp16", "6b-200k", "6b-chat", "6b-v1.5", "6b-q4_0", "6b-q4_1", "6b-q5_0", "6b-q5_1", "6b-q8_0", "6b-q2_K", "6b-q3_K_S", "6b-q3_K_M", "6b-q3_K_L", "6b-q4_K_S", "6b-q4_K_M", "6b-q5_K_S", "6b-q5_K_M", "6b-q6_K", "6b-fp16", "6b-200k-q4_0", "6b-200k-q4_1", "6b-200k-q5_0", "6b-200k-q5_1", "6b-200k-q8_0", "6b-200k-q2_K", "6b-200k-q3_K_S", "6b-200k-q3_K_M", "6b-200k-q3_K_L", "6b-200k-q4_K_S", "6b-200k-q4_K_M", "6b-200k-q5_K_S", "6b-200k-q5_K_M", "6b-200k-q6_K", "6b-200k-fp16", "6b-chat-q4_0", "6b-chat-q4_1", "6b-chat-q5_0", "6b-chat-q5_1", "6b-chat-q8_0", "6b-chat-q2_K", "6b-chat-q3_K_S", "6b-chat-q3_K_M", "6b-chat-q3_K_L", "6b-chat-q4_K_S", "6b-chat-q4_K_M", "6b-chat-q5_K_S", "6b-chat-q5_K_M", "6b-chat-q6_K", "6b-chat-fp16", "6b-v1.5-q4_0", "6b-v1.5-q4_1", "6b-v1.5-q5_0", "6b-v1.5-q5_1", "6b-v1.5-q8_0", "6b-v1.5-q2_K", "6b-v1.5-q3_K_S", "6b-v1.5-q3_K_M", "6b-v1.5-q3_K_L", "6b-v1.5-q4_K_S", "6b-v1.5-q4_K_M", "6b-v1.5-q5_K_S", "6b-v1.5-q5_K_M", "6b-v1.5-q6_K", "6b-v1.5-fp16", "6b-chat-v1.5-q4_0", "6b-chat-v1.5-q4_1", "6b-chat-v1.5-q5_0", "6b-chat-v1.5-q5_1", "6b-chat-v1.5-q8_0", "6b-chat-v1.5-q2_K", "6b-chat-v1.5-q3_K_S", "6b-chat-v1.5-q3_K_M", "6b-chat-v1.5-q3_K_L", "6b-chat-v1.5-q4_K_S", "6b-chat-v1.5-q4_K_M", "6b-chat-v1.5-q5_K_S", "6b-chat-v1.5-q5_K_M", "6b-chat-v1.5-q6_K", "6b-chat-v1.5-fp16"]}, "dolphin-llama3": {"description": "Dolphin 2.9 is a new model with 8B and 70B sizes by Eric Hartford based on Llama 3 that has a variety of instruction, conversational, and coding skills.", "tags": ["latest", "70b", "8b", "256k", "v2.9", "70b-v2.9", "70b-v2.9-q4_0", "70b-v2.9-q4_1", "70b-v2.9-q5_0", "70b-v2.9-q5_1", "70b-v2.9-q8_0", "70b-v2.9-q2_K", "70b-v2.9-q3_K_S", "70b-v2.9-q3_K_M", "70b-v2.9-q3_K_L", "70b-v2.9-q4_K_S", "70b-v2.9-q4_K_M", "70b-v2.9-q5_K_S", "70b-v2.9-q5_K_M", "70b-v2.9-q6_K", "70b-v2.9-fp16", "8b-256k", "8b-v2.9", "8b-256k-v2.9", "8b-v2.9-q4_0", "8b-v2.9-q4_1", "8b-v2.9-q5_0", "8b-v2.9-q5_1", "8b-v2.9-q8_0", "8b-v2.9-q2_K", "8b-v2.9-q3_K_S", "8b-v2.9-q3_K_M", "8b-v2.9-q3_K_L", "8b-v2.9-q4_K_S", "8b-v2.9-q4_K_M", "8b-v2.9-q5_K_S", "8b-v2.9-q5_K_M", "8b-v2.9-q6_K", "8b-v2.9-fp16", "8b-256k-v2.9-q4_0", "8b-256k-v2.9-q4_1", "8b-256k-v2.9-q5_0", "8b-256k-v2.9-q5_1", "8b-256k-v2.9-q8_0", "8b-256k-v2.9-q2_K", "8b-256k-v2.9-q3_K_S", "8b-256k-v2.9-q3_K_M", "8b-256k-v2.9-q3_K_L", "8b-256k-v2.9-q4_K_S", "8b-256k-v2.9-q4_K_M", "8b-256k-v2.9-q5_K_S", "8b-256k-v2.9-q5_K_M", "8b-256k-v2.9-q6_K", "8b-256k-v2.9-fp16"]}, "tinydolphin": {"description": "An experimental 1.1B parameter model trained on the new Dolphin 2.8 dataset by Eric Hartford and based on TinyLlama.", "tags": ["latest", "1.1b", "v2.8", "1.1b-v2.8-q4_0", "1.1b-v2.8-q4_1", "1.1b-v2.8-q5_0", "1.1b-v2.8-q5_1", "1.1b-v2.8-q8_0", "1.1b-v2.8-q2_K", "1.1b-v2.8-q3_K_S", "1.1b-v2.8-q3_K_M", "1.1b-v2.8-q3_K_L", "1.1b-v2.8-q4_K_S", "1.1b-v2.8-q4_K_M", "1.1b-v2.8-q5_K_S", "1.1b-v2.8-q5_K_M", "1.1b-v2.8-q6_K", "1.1b-v2.8-fp16"]}, "wizardcoder": {"description": "State-of-the-art code generation model", "tags": ["latest", "33b", "python", "34b-python", "34b-python-q4_0", "34b-python-q4_1", "34b-python-q5_0", "34b-python-q5_1", "34b-python-q8_0", "34b-python-q2_K", "34b-python-q3_K_S", "34b-python-q3_K_M", "34b-python-q3_K_L", "34b-python-q4_K_S", "34b-python-q4_K_M", "34b-python-q5_K_S", "34b-python-q5_K_M", "34b-python-q6_K", "34b-python-fp16", "33b-v1.1", "33b-v1.1-q4_0", "33b-v1.1-q4_1", "33b-v1.1-q5_0", "33b-v1.1-q5_1", "33b-v1.1-q8_0", "33b-v1.1-q2_K", "33b-v1.1-q3_K_S", "33b-v1.1-q3_K_M", "33b-v1.1-q3_K_L", "33b-v1.1-q4_K_S", "33b-v1.1-q4_K_M", "33b-v1.1-q5_K_S", "33b-v1.1-q5_K_M", "33b-v1.1-q6_K", "33b-v1.1-fp16", "13b-python", "13b-python-q4_0", "13b-python-q4_1", "13b-python-q5_0", "13b-python-q5_1", "13b-python-q8_0", "13b-python-q2_K", "13b-python-q3_K_S", "13b-python-q3_K_M", "13b-python-q3_K_L", "13b-python-q4_K_S", "13b-python-q4_K_M", "13b-python-q5_K_S", "13b-python-q5_K_M", "13b-python-q6_K", "13b-python-fp16", "7b-python", "7b-python-q4_0", "7b-python-q4_1", "7b-python-q5_0", "7b-python-q5_1", "7b-python-q8_0", "7b-python-q2_K", "7b-python-q3_K_S", "7b-python-q3_K_M", "7b-python-q3_K_L", "7b-python-q4_K_S", "7b-python-q4_K_M", "7b-python-q5_K_S", "7b-python-q5_K_M", "7b-python-q6_K", "7b-python-fp16"]}, "mxbai-embed-large": {"description": "State-of-the-art large embedding model from mixedbread.ai", "tags": ["latest", "335m", "v1", "335m-v1-fp16"]}, "stable-code": {"description": "Stable Code 3B is a coding model with instruct and code completion variants on par with models such as Code Llama 7B that are 2.5x larger.", "tags": ["latest", "3b", "code", "instruct", "3b-code", "3b-instruct", "3b-code-q4_0", "3b-code-q4_1", "3b-code-q5_0", "3b-code-q5_1", "3b-code-q8_0", "3b-code-q2_K", "3b-code-q3_K_S", "3b-code-q3_K_M", "3b-code-q3_K_L", "3b-code-q4_K_S", "3b-code-q4_K_M", "3b-code-q5_K_S", "3b-code-q5_K_M", "3b-code-q6_K", "3b-code-fp16", "3b-instruct-q4_0", "3b-instruct-q4_1", "3b-instruct-q5_0", "3b-instruct-q5_1", "3b-instruct-q8_0", "3b-instruct-q2_K", "3b-instruct-q3_K_S", "3b-instruct-q3_K_M", "3b-instruct-q3_K_L", "3b-instruct-q4_K_S", "3b-instruct-q4_K_M", "3b-instruct-q5_K_S", "3b-instruct-q5_K_M", "3b-instruct-q6_K", "3b-instruct-fp16"]}, "neural-chat": {"description": "A fine-tuned model based on Mistral with good coverage of domain and language.", "tags": ["latest", "7b", "7b-v3.1", "7b-v3.2", "7b-v3.3", "7b-v3.1-q4_0", "7b-v3.1-q4_1", "7b-v3.1-q5_0", "7b-v3.1-q5_1", "7b-v3.1-q8_0", "7b-v3.1-q2_K", "7b-v3.1-q3_K_S", "7b-v3.1-q3_K_M", "7b-v3.1-q3_K_L", "7b-v3.1-q4_K_S", "7b-v3.1-q4_K_M", "7b-v3.1-q5_K_S", "7b-v3.1-q5_K_M", "7b-v3.1-q6_K", "7b-v3.1-fp16", "7b-v3.2-q4_0", "7b-v3.2-q4_1", "7b-v3.2-q5_0", "7b-v3.2-q5_1", "7b-v3.2-q8_0", "7b-v3.2-q2_K", "7b-v3.2-q3_K_S", "7b-v3.2-q3_K_M", "7b-v3.2-q3_K_L", "7b-v3.2-q4_K_S", "7b-v3.2-q4_K_M", "7b-v3.2-q5_K_S", "7b-v3.2-q5_K_M", "7b-v3.2-q6_K", "7b-v3.2-fp16", "7b-v3.3-q4_0", "7b-v3.3-q4_1", "7b-v3.3-q5_0", "7b-v3.3-q5_1", "7b-v3.3-q8_0", "7b-v3.3-q2_K", "7b-v3.3-q3_K_S", "7b-v3.3-q3_K_M", "7b-v3.3-q3_K_L", "7b-v3.3-q4_K_S", "7b-v3.3-q4_K_M", "7b-v3.3-q5_K_S", "7b-v3.3-q5_K_M", "7b-v3.3-q6_K", "7b-v3.3-fp16"]}, "phind-codellama": {"description": "Code generation model based on Code Llama.", "tags": ["latest", "34b", "34b-python", "34b-v2", "34b-q4_0", "34b-q4_1", "34b-q5_0", "34b-q5_1", "34b-q8_0", "34b-q2_K", "34b-q3_K_S", "34b-q3_K_M", "34b-q3_K_L", "34b-q4_K_S", "34b-q4_K_M", "34b-q5_K_S", "34b-q5_K_M", "34b-q6_K", "34b-fp16", "34b-python-q4_0", "34b-python-q4_1", "34b-python-q5_0", "34b-python-q5_1", "34b-python-q8_0", "34b-python-q2_K", "34b-python-q3_K_S", "34b-python-q3_K_M", "34b-python-q3_K_L", "34b-python-q4_K_S", "34b-python-q4_K_M", "34b-python-q5_K_S", "34b-python-q5_K_M", "34b-python-q6_K", "34b-python-fp16", "34b-v2-q4_0", "34b-v2-q4_1", "34b-v2-q5_0", "34b-v2-q5_1", "34b-v2-q8_0", "34b-v2-q2_K", "34b-v2-q3_K_S", "34b-v2-q3_K_M", "34b-v2-q3_K_L", "34b-v2-q4_K_S", "34b-v2-q4_K_M", "34b-v2-q5_K_S", "34b-v2-q5_K_M", "34b-v2-q6_K", "34b-v2-fp16"]}, "wizard-math": {"description": "Model focused on math and logic problems", "tags": ["latest", "70b", "13b", "7b", "70b-q4_0", "70b-q4_1", "70b-q5_0", "70b-q5_1", "70b-q8_0", "70b-q2_K", "70b-q3_K_S", "70b-q3_K_M", "70b-q3_K_L", "70b-q4_K_S", "70b-q4_K_M", "70b-q5_K_S", "70b-q5_K_M", "70b-q6_K", "70b-fp16", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16", "7b-v1.1-q4_0", "7b-v1.1-q4_1", "7b-v1.1-q5_0", "7b-v1.1-q5_1", "7b-v1.1-q8_0", "7b-v1.1-q2_K", "7b-v1.1-q3_K_S", "7b-v1.1-q3_K_M", "7b-v1.1-q3_K_L", "7b-v1.1-q4_K_S", "7b-v1.1-q4_K_M", "7b-v1.1-q5_K_S", "7b-v1.1-q5_K_M", "7b-v1.1-q6_K", "7b-v1.1-fp16"]}, "starling-lm": {"description": "Starling is a large language model trained by reinforcement learning from AI feedback focused on improving chatbot helpfulness.", "tags": ["latest", "7b", "alpha", "beta", "7b-alpha", "7b-beta", "7b-alpha-q4_0", "7b-alpha-q4_1", "7b-alpha-q5_0", "7b-alpha-q5_1", "7b-alpha-q8_0", "7b-alpha-q2_K", "7b-alpha-q3_K_S", "7b-alpha-q3_K_M", "7b-alpha-q3_K_L", "7b-alpha-q4_K_S", "7b-alpha-q4_K_M", "7b-alpha-q5_K_S", "7b-alpha-q5_K_M", "7b-alpha-q6_K", "7b-alpha-fp16", "7b-beta-q4_0", "7b-beta-q4_1", "7b-beta-q5_0", "7b-beta-q5_1", "7b-beta-q8_0", "7b-beta-q2_K", "7b-beta-q3_K_S", "7b-beta-q3_K_M", "7b-beta-q3_K_L", "7b-beta-q4_K_S", "7b-beta-q4_K_M", "7b-beta-q5_K_S", "7b-beta-q5_K_M", "7b-beta-q6_K", "7b-beta-fp16"]}, "falcon": {"description": "A large language model built by the Technology Innovation Institute (TII) for use in summarization, text generation, and chat bots.", "tags": ["latest", "180b", "40b", "7b", "instruct", "text", "180b-chat", "180b-text", "180b-chat-q4_0", "180b-text-q4_0", "40b-instruct", "40b-text", "40b-instruct-q4_0", "40b-instruct-q4_1", "40b-instruct-q5_0", "40b-instruct-q5_1", "40b-instruct-q8_0", "40b-instruct-fp16", "40b-text-q4_0", "40b-text-q4_1", "40b-text-q5_0", "40b-text-q5_1", "40b-text-q8_0", "40b-text-fp16", "7b-instruct", "7b-text", "7b-instruct-q4_0", "7b-instruct-q4_1", "7b-instruct-q5_0", "7b-instruct-q5_1", "7b-instruct-q8_0", "7b-instruct-fp16", "7b-text-q4_0", "7b-text-q4_1", "7b-text-q5_0", "7b-text-q5_1", "7b-text-q8_0", "7b-text-fp16"]}, "dolphincoder": {"description": "A 7B and 15B uncensored variant of the Dolphin model family that excels at coding, based on StarCoder2.", "tags": ["latest", "15b", "7b", "15b-starcoder2", "15b-starcoder2-q4_0", "15b-starcoder2-q4_1", "15b-starcoder2-q5_0", "15b-starcoder2-q5_1", "15b-starcoder2-q8_0", "15b-starcoder2-q2_K", "15b-starcoder2-q3_K_S", "15b-starcoder2-q3_K_M", "15b-starcoder2-q3_K_L", "15b-starcoder2-q4_K_S", "15b-starcoder2-q4_K_M", "15b-starcoder2-q5_K_S", "15b-starcoder2-q5_K_M", "15b-starcoder2-q6_K", "15b-starcoder2-fp16", "7b-starcoder2", "7b-starcoder2-q4_0", "7b-starcoder2-q4_1", "7b-starcoder2-q5_0", "7b-starcoder2-q5_1", "7b-starcoder2-q8_0", "7b-starcoder2-q2_K", "7b-starcoder2-q3_K_S", "7b-starcoder2-q3_K_M", "7b-starcoder2-q3_K_L", "7b-starcoder2-q4_K_S", "7b-starcoder2-q4_K_M", "7b-starcoder2-q5_K_S", "7b-starcoder2-q5_K_M", "7b-starcoder2-q6_K", "7b-starcoder2-fp16"]}, "nous-hermes": {"description": "General use models based on Llama and Llama 2 from Nous Research.", "tags": ["latest", "13b", "7b", "70b-llama2-q4_0", "70b-llama2-q4_1", "70b-llama2-q5_0", "70b-llama2-q5_1", "70b-llama2-q2_K", "70b-llama2-q3_K_S", "70b-llama2-q3_K_M", "70b-llama2-q3_K_L", "70b-llama2-q4_K_S", "70b-llama2-q4_K_M", "70b-llama2-q5_K_M", "70b-llama2-q6_K", "70b-llama2-fp16", "13b-llama2", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16", "13b-llama2-q4_0", "13b-llama2-q4_1", "13b-llama2-q5_0", "13b-llama2-q5_1", "13b-llama2-q8_0", "13b-llama2-q2_K", "13b-llama2-q3_K_S", "13b-llama2-q3_K_M", "13b-llama2-q3_K_L", "13b-llama2-q4_K_S", "13b-llama2-q4_K_M", "13b-llama2-q5_K_S", "13b-llama2-q5_K_M", "13b-llama2-q6_K", "13b-llama2-fp16", "7b-llama2", "7b-llama2-q4_0", "7b-llama2-q4_1", "7b-llama2-q5_0", "7b-llama2-q5_1", "7b-llama2-q8_0", "7b-llama2-q2_K", "7b-llama2-q3_K_S", "7b-llama2-q3_K_M", "7b-llama2-q3_K_L", "7b-llama2-q4_K_S", "7b-llama2-q4_K_M", "7b-llama2-q5_K_S", "7b-llama2-q5_K_M", "7b-llama2-q6_K", "7b-llama2-fp16"]}, "orca2": {"description": "Orca 2 is built by Microsoft research, and are a fine-tuned version of Meta's Llama 2 models. The model is designed to excel particularly in reasoning.", "tags": ["latest", "13b", "7b", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "stablelm2": {"description": "Stable LM 2 is a state-of-the-art 1.6B and 12B parameter language model trained on multilingual data in English, Spanish, German, Italian, French, Portuguese, and Dutch.", "tags": ["latest", "12b", "1.6b", "chat", "zephyr", "12b-chat", "12b-text", "12b-q4_0", "12b-q4_1", "12b-q5_0", "12b-q5_1", "12b-q8_0", "12b-q2_K", "12b-q3_K_S", "12b-q3_K_M", "12b-q3_K_L", "12b-q4_K_S", "12b-q4_K_M", "12b-q5_K_S", "12b-q5_K_M", "12b-q6_K", "12b-fp16", "12b-chat-q4_0", "12b-chat-q4_1", "12b-chat-q5_0", "12b-chat-q5_1", "12b-chat-q8_0", "12b-chat-q2_K", "12b-chat-q3_K_S", "12b-chat-q3_K_M", "12b-chat-q3_K_L", "12b-chat-q4_K_S", "12b-chat-q4_K_M", "12b-chat-q5_K_S", "12b-chat-q5_K_M", "12b-chat-q6_K", "12b-chat-fp16", "1.6b-chat", "1.6b-zephyr", "1.6b-q4_0", "1.6b-q4_1", "1.6b-q5_0", "1.6b-q5_1", "1.6b-q8_0", "1.6b-q2_K", "1.6b-q3_K_S", "1.6b-q3_K_M", "1.6b-q3_K_L", "1.6b-q4_K_S", "1.6b-q4_K_M", "1.6b-q5_K_S", "1.6b-q5_K_M", "1.6b-q6_K", "1.6b-fp16", "1.6b-chat-q4_0", "1.6b-chat-q4_1", "1.6b-chat-q5_0", "1.6b-chat-q5_1", "1.6b-chat-q8_0", "1.6b-chat-q2_K", "1.6b-chat-q3_K_S", "1.6b-chat-q3_K_M", "1.6b-chat-q3_K_L", "1.6b-chat-q4_K_S", "1.6b-chat-q4_K_M", "1.6b-chat-q5_K_S", "1.6b-chat-q5_K_M", "1.6b-chat-q6_K", "1.6b-chat-fp16", "1.6b-zephyr-q4_0", "1.6b-zephyr-q4_1", "1.6b-zephyr-q5_0", "1.6b-zephyr-q5_1", "1.6b-zephyr-q8_0", "1.6b-zephyr-q2_K", "1.6b-zephyr-q3_K_S", "1.6b-zephyr-q3_K_M", "1.6b-zephyr-q3_K_L", "1.6b-zephyr-q4_K_S", "1.6b-zephyr-q4_K_M", "1.6b-zephyr-q5_K_S", "1.6b-zephyr-q5_K_M", "1.6b-zephyr-q6_K", "1.6b-zephyr-fp16"]}, "sqlcoder": {"description": "SQLCoder is a code completion model fined-tuned on StarCoder for SQL generation tasks", "tags": ["latest", "15b", "7b", "70b-alpha-q4_0", "70b-alpha-q4_1", "70b-alpha-q5_0", "70b-alpha-q5_1", "70b-alpha-q8_0", "70b-alpha-q2_K", "70b-alpha-q3_K_S", "70b-alpha-q3_K_M", "70b-alpha-q3_K_L", "70b-alpha-q4_K_S", "70b-alpha-q4_K_M", "70b-alpha-q5_K_S", "70b-alpha-q5_K_M", "70b-alpha-q6_K", "70b-alpha-fp16", "15b-q4_0", "15b-q4_1", "15b-q5_0", "15b-q5_1", "15b-q8_0", "15b-q2_K", "15b-q3_K_S", "15b-q3_K_M", "15b-q3_K_L", "15b-q4_K_S", "15b-q4_K_M", "15b-q5_K_S", "15b-q5_K_M", "15b-q6_K", "15b-fp16", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "dolphin-phi": {"description": "2.7B uncensored Dolphin model by Eric Hartford, based on the Phi language model by Microsoft Research.", "tags": ["latest", "2.7b", "2.7b-v2.6", "2.7b-v2.6-q4_0", "2.7b-v2.6-q5_0", "2.7b-v2.6-q8_0", "2.7b-v2.6-q2_K", "2.7b-v2.6-q3_K_S", "2.7b-v2.6-q3_K_M", "2.7b-v2.6-q3_K_L", "2.7b-v2.6-q4_K_S", "2.7b-v2.6-q4_K_M", "2.7b-v2.6-q5_K_S", "2.7b-v2.6-q5_K_M", "2.7b-v2.6-q6_K"]}, "solar": {"description": "A compact, yet powerful 10.7B large language model designed for single-turn conversation.", "tags": ["latest", "10.7b", "10.7b-instruct-v1-q4_0", "10.7b-instruct-v1-q4_1", "10.7b-instruct-v1-q5_0", "10.7b-instruct-v1-q5_1", "10.7b-instruct-v1-q8_0", "10.7b-instruct-v1-q2_K", "10.7b-instruct-v1-q3_K_S", "10.7b-instruct-v1-q3_K_M", "10.7b-instruct-v1-q3_K_L", "10.7b-instruct-v1-q4_K_S", "10.7b-instruct-v1-q4_K_M", "10.7b-instruct-v1-q5_K_S", "10.7b-instruct-v1-q5_K_M", "10.7b-instruct-v1-q6_K", "10.7b-instruct-v1-fp16", "10.7b-text-v1-q4_0", "10.7b-text-v1-q4_1", "10.7b-text-v1-q5_0", "10.7b-text-v1-q5_1", "10.7b-text-v1-q8_0", "10.7b-text-v1-q2_K", "10.7b-text-v1-q3_K_S", "10.7b-text-v1-q3_K_M", "10.7b-text-v1-q3_K_L", "10.7b-text-v1-q4_K_S", "10.7b-text-v1-q4_K_M", "10.7b-text-v1-q5_K_S", "10.7b-text-v1-q5_K_M", "10.7b-text-v1-q6_K", "10.7b-text-v1-fp16"]}, "yarn-llama2": {"description": "An extension of Llama 2 that supports a context of up to 128k tokens.", "tags": ["latest", "13b", "7b", "13b-128k", "13b-64k", "13b-128k-q4_0", "13b-128k-q4_1", "13b-128k-q5_0", "13b-128k-q5_1", "13b-128k-q8_0", "13b-128k-q2_K", "13b-128k-q3_K_S", "13b-128k-q3_K_M", "13b-128k-q3_K_L", "13b-128k-q4_K_S", "13b-128k-q4_K_M", "13b-128k-q5_K_S", "13b-128k-q5_K_M", "13b-128k-q6_K", "13b-128k-fp16", "13b-64k-q4_0", "13b-64k-q4_1", "13b-64k-q5_0", "13b-64k-q5_1", "13b-64k-q8_0", "13b-64k-q2_K", "13b-64k-q3_K_S", "13b-64k-q3_K_M", "13b-64k-q3_K_L", "13b-64k-q4_K_S", "13b-64k-q4_K_M", "13b-64k-q5_K_S", "13b-64k-q5_K_M", "13b-64k-q6_K", "13b-64k-fp16", "7b-128k", "7b-64k", "7b-128k-q4_0", "7b-128k-q4_1", "7b-128k-q5_0", "7b-128k-q5_1", "7b-128k-q8_0", "7b-128k-q2_K", "7b-128k-q3_K_S", "7b-128k-q3_K_M", "7b-128k-q3_K_L", "7b-128k-q4_K_S", "7b-128k-q4_K_M", "7b-128k-q5_K_S", "7b-128k-q5_K_M", "7b-128k-q6_K", "7b-128k-fp16", "7b-64k-q4_0", "7b-64k-q4_1", "7b-64k-q5_0", "7b-64k-q5_1", "7b-64k-q8_0", "7b-64k-q2_K", "7b-64k-q3_K_S", "7b-64k-q3_K_M", "7b-64k-q3_K_L", "7b-64k-q4_K_S", "7b-64k-q4_K_M", "7b-64k-q5_K_S", "7b-64k-q5_K_M", "7b-64k-q6_K", "7b-64k-fp16"]}, "deepseek-llm": {"description": "An advanced language model crafted with 2 trillion bilingual tokens.", "tags": ["latest", "67b", "7b", "67b-base", "67b-chat", "67b-base-q4_0", "67b-base-q4_1", "67b-base-q5_0", "67b-base-q5_1", "67b-base-q8_0", "67b-base-q2_K", "67b-base-q3_K_S", "67b-base-q3_K_M", "67b-base-q3_K_L", "67b-base-q4_K_S", "67b-base-q4_K_M", "67b-base-q5_K_S", "67b-base-q5_K_M", "67b-base-q6_K", "67b-base-fp16", "67b-chat-q4_0", "67b-chat-q4_1", "67b-chat-q5_0", "67b-chat-q5_1", "67b-chat-q2_K", "67b-chat-q3_K_S", "67b-chat-q3_K_M", "67b-chat-q3_K_L", "67b-chat-q4_K_S", "67b-chat-q4_K_M", "67b-chat-q5_K_S", "67b-chat-fp16", "7b-base", "7b-chat", "7b-base-q4_0", "7b-base-q4_1", "7b-base-q5_0", "7b-base-q5_1", "7b-base-q8_0", "7b-base-q2_K", "7b-base-q3_K_S", "7b-base-q3_K_M", "7b-base-q3_K_L", "7b-base-q4_K_S", "7b-base-q4_K_M", "7b-base-q5_K_S", "7b-base-q5_K_M", "7b-base-q6_K", "7b-base-fp16", "7b-chat-q4_0", "7b-chat-q4_1", "7b-chat-q5_0", "7b-chat-q5_1", "7b-chat-q8_0", "7b-chat-q2_K", "7b-chat-q3_K_S", "7b-chat-q3_K_M", "7b-chat-q3_K_L", "7b-chat-q4_K_S", "7b-chat-q4_K_M", "7b-chat-q5_K_S", "7b-chat-q5_K_M", "7b-chat-q6_K", "7b-chat-fp16"]}, "codeqwen": {"description": "CodeQwen1.5 is a large language model pretrained on a large amount of code data.", "tags": ["latest", "7b", "chat", "code", "v1.5", "7b-chat", "7b-code", "7b-chat-v1.5-q4_0", "7b-chat-v1.5-q4_1", "7b-chat-v1.5-q5_0", "7b-chat-v1.5-q5_1", "7b-chat-v1.5-q8_0", "7b-chat-v1.5-fp16", "7b-code-v1.5-q4_0", "7b-code-v1.5-q4_1", "7b-code-v1.5-q5_0", "7b-code-v1.5-q5_1", "7b-code-v1.5-q8_0", "7b-code-v1.5-fp16", "v1.5-chat", "v1.5-code"]}, "bakllava": {"description": "BakLLaVA is a multimodal model consisting of the Mistral 7B base model augmented with the LLaVA architecture.", "tags": ["latest", "7b", "7b-v1-q4_0", "7b-v1-q4_1", "7b-v1-q5_0", "7b-v1-q5_1", "7b-v1-q8_0", "7b-v1-q2_K", "7b-v1-q3_K_S", "7b-v1-q3_K_M", "7b-v1-q3_K_L", "7b-v1-q4_K_S", "7b-v1-q4_K_M", "7b-v1-q5_K_S", "7b-v1-q5_K_M", "7b-v1-q6_K", "7b-v1-fp16"]}, "all-minilm": {"description": "Embedding models on very large sentence level datasets.", "tags": ["latest", "33m", "22m", "l12", "l6", "v2", "33m-l12-v2-fp16", "22m-l6-v2-fp16", "l6-v2", "l12-v2"]}, "samantha-mistral": {"description": "A companion assistant trained in philosophy, psychology, and personal relationships. Based on Mistral.", "tags": ["latest", "7b", "7b-text", "7b-instruct-q4_0", "7b-instruct-q4_1", "7b-instruct-q5_0", "7b-instruct-q5_1", "7b-instruct-q8_0", "7b-instruct-q2_K", "7b-instruct-q3_K_S", "7b-instruct-q3_K_M", "7b-instruct-q3_K_L", "7b-instruct-q4_K_S", "7b-instruct-q4_K_M", "7b-instruct-q5_K_S", "7b-instruct-q5_K_M", "7b-instruct-q6_K", "7b-instruct-fp16", "7b-text-q4_0", "7b-text-q4_1", "7b-text-q5_0", "7b-text-q5_1", "7b-text-q8_0", "7b-text-q2_K", "7b-text-q3_K_S", "7b-text-q3_K_M", "7b-text-q3_K_L", "7b-text-q4_K_S", "7b-text-q4_K_M", "7b-text-q5_K_S", "7b-text-q5_K_M", "7b-text-q6_K", "7b-text-fp16", "7b-v1.2-text", "7b-v1.2-text-q4_0", "7b-v1.2-text-q4_1", "7b-v1.2-text-q5_0", "7b-v1.2-text-q5_1", "7b-v1.2-text-q8_0", "7b-v1.2-text-q2_K", "7b-v1.2-text-q3_K_S", "7b-v1.2-text-q3_K_M", "7b-v1.2-text-q3_K_L", "7b-v1.2-text-q4_K_S", "7b-v1.2-text-q4_K_M", "7b-v1.2-text-q5_K_S", "7b-v1.2-text-q5_K_M", "7b-v1.2-text-q6_K", "7b-v1.2-text-fp16"]}, "llama3-gradient": {"description": "This model extends LLama-3 8B's context length from 8k to over 1m tokens.", "tags": ["latest", "70b", "8b", "1048k", "instruct", "70b-instruct-1048k-q4_0", "70b-instruct-1048k-q4_1", "70b-instruct-1048k-q5_0", "70b-instruct-1048k-q5_1", "70b-instruct-1048k-q8_0", "70b-instruct-1048k-q2_K", "70b-instruct-1048k-q3_K_S", "70b-instruct-1048k-q3_K_M", "70b-instruct-1048k-q3_K_L", "70b-instruct-1048k-q4_K_S", "70b-instruct-1048k-q4_K_M", "70b-instruct-1048k-q5_K_S", "70b-instruct-1048k-q5_K_M", "70b-instruct-1048k-q6_K", "70b-instruct-1048k-fp16", "8b-instruct-1048k-q4_0", "8b-instruct-1048k-q4_1", "8b-instruct-1048k-q5_0", "8b-instruct-1048k-q5_1", "8b-instruct-1048k-q8_0", "8b-instruct-1048k-q2_K", "8b-instruct-1048k-q3_K_S", "8b-instruct-1048k-q3_K_M", "8b-instruct-1048k-q3_K_L", "8b-instruct-1048k-q4_K_S", "8b-instruct-1048k-q4_K_M", "8b-instruct-1048k-q5_K_S", "8b-instruct-1048k-q5_K_M", "8b-instruct-1048k-q6_K", "8b-instruct-1048k-fp16"]}, "medllama2": {"description": "Fine-tuned Llama 2 model to answer medical questions based on an open source medical dataset.", "tags": ["latest", "7b", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "wizardlm-uncensored": {"description": "Uncensored version of Wizard LM model", "tags": ["latest", "13b", "13b-llama2", "13b-llama2-q4_0", "13b-llama2-q4_1", "13b-llama2-q5_0", "13b-llama2-q5_1", "13b-llama2-q8_0", "13b-llama2-q2_K", "13b-llama2-q3_K_S", "13b-llama2-q3_K_M", "13b-llama2-q3_K_L", "13b-llama2-q4_K_S", "13b-llama2-q4_K_M", "13b-llama2-q5_K_S", "13b-llama2-q5_K_M", "13b-llama2-q6_K", "13b-llama2-fp16"]}, "xwinlm": {"description": "Conversational model based on Llama 2 that performs competitively on various benchmarks.", "tags": ["latest", "13b", "7b", "70b-v0.1", "70b-v0.1-q4_0", "70b-v0.1-q4_1", "70b-v0.1-q5_0", "70b-v0.1-q5_1", "70b-v0.1-q8_0", "70b-v0.1-q2_K", "70b-v0.1-q3_K_S", "70b-v0.1-q3_K_M", "70b-v0.1-q3_K_L", "70b-v0.1-q4_K_S", "70b-v0.1-q4_K_M", "70b-v0.1-q5_K_S", "70b-v0.1-q6_K", "70b-v0.1-fp16", "13b-v0.1", "13b-v0.2", "13b-v0.1-q4_0", "13b-v0.1-q4_1", "13b-v0.1-q5_0", "13b-v0.1-q5_1", "13b-v0.1-q8_0", "13b-v0.1-q2_K", "13b-v0.1-q3_K_S", "13b-v0.1-q3_K_M", "13b-v0.1-q3_K_L", "13b-v0.1-q4_K_S", "13b-v0.1-q4_K_M", "13b-v0.1-q5_K_S", "13b-v0.1-q5_K_M", "13b-v0.1-q6_K", "13b-v0.1-fp16", "13b-v0.2-q4_0", "13b-v0.2-q4_1", "13b-v0.2-q5_0", "13b-v0.2-q5_1", "13b-v0.2-q8_0", "13b-v0.2-q2_K", "13b-v0.2-q3_K_S", "13b-v0.2-q3_K_M", "13b-v0.2-q3_K_L", "13b-v0.2-q4_K_S", "13b-v0.2-q4_K_M", "13b-v0.2-q5_K_S", "13b-v0.2-q5_K_M", "13b-v0.2-q6_K", "13b-v0.2-fp16", "7b-v0.1", "7b-v0.2", "7b-v0.1-q4_0", "7b-v0.1-q4_1", "7b-v0.1-q5_0", "7b-v0.1-q5_1", "7b-v0.1-q8_0", "7b-v0.1-q2_K", "7b-v0.1-q3_K_S", "7b-v0.1-q3_K_M", "7b-v0.1-q3_K_L", "7b-v0.1-q4_K_S", "7b-v0.1-q4_K_M", "7b-v0.1-q5_K_S", "7b-v0.1-q5_K_M", "7b-v0.1-q6_K", "7b-v0.1-fp16", "7b-v0.2-q4_0", "7b-v0.2-q4_1", "7b-v0.2-q5_0", "7b-v0.2-q8_0", "7b-v0.2-q2_K", "7b-v0.2-q3_K_S", "7b-v0.2-q3_K_L", "7b-v0.2-q4_K_S", "7b-v0.2-q4_K_M", "7b-v0.2-q5_K_S", "7b-v0.2-q5_K_M", "7b-v0.2-q6_K", "7b-v0.2-fp16"]}, "nous-hermes2-mixtral": {"description": "The Nous Hermes 2 model from Nous Research, now trained over Mixtral.", "tags": ["latest", "8x7b", "dpo", "8x7b-dpo-q4_0", "8x7b-dpo-q4_1", "8x7b-dpo-q5_0", "8x7b-dpo-q5_1", "8x7b-dpo-q8_0", "8x7b-dpo-q2_K", "8x7b-dpo-q3_K_S", "8x7b-dpo-q3_K_M", "8x7b-dpo-q3_K_L", "8x7b-dpo-q4_K_S", "8x7b-dpo-q4_K_M", "8x7b-dpo-q5_K_S", "8x7b-dpo-q5_K_M", "8x7b-dpo-q6_K", "8x7b-dpo-fp16"]}, "stable-beluga": {"description": "Llama 2 based model fine tuned on an Orca-style dataset. Originally called Free Willy.", "tags": ["latest", "70b", "13b", "7b", "70b-q4_0", "70b-q4_1", "70b-q5_0", "70b-q5_1", "70b-q8_0", "70b-q2_K", "70b-q3_K_S", "70b-q3_K_M", "70b-q3_K_L", "70b-q4_K_S", "70b-q4_K_M", "70b-q5_K_S", "70b-q5_K_M", "70b-q6_K", "70b-fp16", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "wizardlm": {"description": "General use model based on Llama 2.", "tags": ["70b-llama2-q4_0", "70b-llama2-q4_1", "70b-llama2-q5_0", "70b-llama2-q8_0", "70b-llama2-q2_K", "70b-llama2-q3_K_S", "70b-llama2-q3_K_M", "70b-llama2-q3_K_L", "70b-llama2-q4_K_S", "70b-llama2-q4_K_M", "70b-llama2-q5_K_S", "70b-llama2-q5_K_M", "70b-llama2-q6_K", "30b-q4_0", "30b-q4_1", "30b-q5_0", "30b-q5_1", "30b-q8_0", "30b-q2_K", "30b-q3_K_S", "30b-q3_K_M", "30b-q3_K_L", "30b-q4_K_S", "30b-q4_K_M", "30b-q5_K_S", "30b-q5_K_M", "30b-q6_K", "30b-fp16", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16", "13b-llama2-q4_0", "13b-llama2-q4_1", "13b-llama2-q5_0", "13b-llama2-q5_1", "13b-llama2-q8_0", "13b-llama2-q2_K", "13b-llama2-q3_K_S", "13b-llama2-q3_K_M", "13b-llama2-q3_K_L", "13b-llama2-q4_K_S", "13b-llama2-q4_K_M", "13b-llama2-q5_K_S", "13b-llama2-q5_K_M", "13b-llama2-q6_K", "13b-llama2-fp16", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "codeup": {"description": "Great code generation model based on Llama2.", "tags": ["latest", "13b", "13b-llama2", "13b-llama2-chat", "13b-llama2-chat-q4_0", "13b-llama2-chat-q4_1", "13b-llama2-chat-q5_0", "13b-llama2-chat-q5_1", "13b-llama2-chat-q8_0", "13b-llama2-chat-q2_K", "13b-llama2-chat-q3_K_S", "13b-llama2-chat-q3_K_M", "13b-llama2-chat-q3_K_L", "13b-llama2-chat-q4_K_S", "13b-llama2-chat-q4_K_M", "13b-llama2-chat-q5_K_S", "13b-llama2-chat-q5_K_M", "13b-llama2-chat-q6_K", "13b-llama2-chat-fp16"]}, "yarn-mistral": {"description": "An extension of Mistral to support context windows of 64K or 128K.", "tags": ["latest", "7b", "7b-128k", "7b-64k", "7b-128k-q4_0", "7b-128k-q4_1", "7b-128k-q5_0", "7b-128k-q5_1", "7b-128k-q8_0", "7b-128k-q2_K", "7b-128k-q3_K_S", "7b-128k-q3_K_M", "7b-128k-q3_K_L", "7b-128k-q4_K_S", "7b-128k-q4_K_M", "7b-128k-q5_K_S", "7b-128k-q5_K_M", "7b-128k-q6_K", "7b-128k-fp16", "7b-64k-q4_0", "7b-64k-q4_1", "7b-64k-q5_0", "7b-64k-q5_1", "7b-64k-q8_0", "7b-64k-q2_K", "7b-64k-q3_K_S", "7b-64k-q3_K_M", "7b-64k-q3_K_L", "7b-64k-q4_K_S", "7b-64k-q4_K_M", "7b-64k-q5_K_S", "7b-64k-q5_K_M", "7b-64k-q6_K"]}, "everythinglm": {"description": "Uncensored Llama2 based model with support for a 16K context window.", "tags": ["latest", "13b", "13b-16k", "13b-16k-q4_0", "13b-16k-q4_1", "13b-16k-q5_0", "13b-16k-q5_1", "13b-16k-q8_0", "13b-16k-q2_K", "13b-16k-q3_K_S", "13b-16k-q3_K_M", "13b-16k-q3_K_L", "13b-16k-q4_K_S", "13b-16k-q4_K_M", "13b-16k-q5_K_S", "13b-16k-q5_K_M", "13b-16k-q6_K", "13b-16k-fp16"]}, "meditron": {"description": "Open-source medical large language model adapted from Llama 2 to the medical domain.", "tags": ["latest", "70b", "7b", "70b-q4_0", "70b-q4_1", "70b-q5_1", "70b-q4_K_S", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "llama-pro": {"description": "An expansion of Llama 2 that specializes in integrating both general language understanding and domain-specific knowledge, particularly in programming and mathematics.", "tags": ["latest", "instruct", "text", "8b-instruct-q4_0", "8b-instruct-q4_1", "8b-instruct-q5_0", "8b-instruct-q5_1", "8b-instruct-q8_0", "8b-instruct-q2_K", "8b-instruct-q3_K_S", "8b-instruct-q3_K_M", "8b-instruct-q3_K_L", "8b-instruct-q4_K_S", "8b-instruct-q4_K_M", "8b-instruct-q5_K_S", "8b-instruct-q5_K_M", "8b-instruct-q6_K", "8b-instruct-fp16", "8b-text-q4_0", "8b-text-q4_1", "8b-text-q5_0", "8b-text-q5_1", "8b-text-q8_0", "8b-text-q2_K", "8b-text-q3_K_S", "8b-text-q3_K_M", "8b-text-q3_K_L", "8b-text-q4_K_S", "8b-text-q4_K_M", "8b-text-q5_K_S", "8b-text-q5_K_M", "8b-text-q6_K", "8b-text-fp16"]}, "magicoder": {"description": "🎩 Magicoder is a family of 7B parameter models trained on 75K synthetic instruction data using OSS-Instruct, a novel approach to enlightening LLMs with open-source code snippets.", "tags": ["latest", "7b", "7b-s-cl", "7b-s-cl-q4_0", "7b-s-cl-q4_1", "7b-s-cl-q5_0", "7b-s-cl-q5_1", "7b-s-cl-q8_0", "7b-s-cl-q2_K", "7b-s-cl-q3_K_S", "7b-s-cl-q3_K_M", "7b-s-cl-q3_K_L", "7b-s-cl-q4_K_S", "7b-s-cl-q4_K_M", "7b-s-cl-q5_K_S", "7b-s-cl-q5_K_M", "7b-s-cl-q6_K", "7b-s-cl-fp16"]}, "stablelm-zephyr": {"description": "A lightweight chat model allowing accurate, and responsive output without requiring high-end hardware.", "tags": ["latest", "3b", "3b-q4_0", "3b-q4_1", "3b-q5_0", "3b-q5_1", "3b-q8_0", "3b-q2_K", "3b-q3_K_S", "3b-q3_K_M", "3b-q3_K_L", "3b-q4_K_S", "3b-q4_K_M", "3b-q5_K_S", "3b-q5_K_M", "3b-q6_K", "3b-fp16"]}, "nexusraven": {"description": "Nexus Raven is a 13B instruction tuned model for function calling tasks.", "tags": ["latest", "13b", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16", "13b-v2-q4_0", "13b-v2-q4_1", "13b-v2-q5_0", "13b-v2-q5_1", "13b-v2-q8_0", "13b-v2-q2_K", "13b-v2-q3_K_S", "13b-v2-q3_K_M", "13b-v2-q3_K_L", "13b-v2-q4_K_S", "13b-v2-q4_K_M", "13b-v2-q5_K_S", "13b-v2-q5_K_M", "13b-v2-q6_K", "13b-v2-fp16"]}, "codebooga": {"description": "A high-performing code instruct model created by merging two existing code models.", "tags": ["latest", "34b", "34b-v0.1-q4_0", "34b-v0.1-q4_1", "34b-v0.1-q5_0", "34b-v0.1-q5_1", "34b-v0.1-q8_0", "34b-v0.1-q2_K", "34b-v0.1-q3_K_S", "34b-v0.1-q3_K_M", "34b-v0.1-q3_K_L", "34b-v0.1-q4_K_M", "34b-v0.1-q5_K_S", "34b-v0.1-q5_K_M", "34b-v0.1-q6_K", "34b-v0.1-fp16"]}, "mistrallite": {"description": "MistralLite is a fine-tuned model based on Mistral with enhanced capabilities of processing long contexts.", "tags": ["latest", "7b", "7b-v0.1-q4_0", "7b-v0.1-q4_1", "7b-v0.1-q5_0", "7b-v0.1-q5_1", "7b-v0.1-q8_0", "7b-v0.1-q2_K", "7b-v0.1-q3_K_S", "7b-v0.1-q3_K_M", "7b-v0.1-q3_K_L", "7b-v0.1-q4_K_S", "7b-v0.1-q4_K_M", "7b-v0.1-q5_K_S", "7b-v0.1-q5_K_M", "7b-v0.1-q6_K", "7b-v0.1-fp16"]}, "llama3-chatqa": {"description": "A model from NVIDIA based on Llama 3 that excels at conversational question answering (QA) and retrieval-augmented generation (RAG).", "tags": ["latest", "70b", "8b", "70b-v1.5", "70b-v1.5-q4_0", "70b-v1.5-q4_1", "70b-v1.5-q5_0", "70b-v1.5-q5_1", "70b-v1.5-q8_0", "70b-v1.5-q2_K", "70b-v1.5-q3_K_S", "70b-v1.5-q3_K_M", "70b-v1.5-q3_K_L", "70b-v1.5-q4_K_S", "70b-v1.5-q4_K_M", "70b-v1.5-q5_K_S", "70b-v1.5-q5_K_M", "70b-v1.5-q6_K", "70b-v1.5-fp16", "8b-v1.5", "8b-v1.5-q4_0", "8b-v1.5-q4_1", "8b-v1.5-q5_0", "8b-v1.5-q5_1", "8b-v1.5-q8_0", "8b-v1.5-q2_K", "8b-v1.5-q3_K_S", "8b-v1.5-q3_K_M", "8b-v1.5-q3_K_L", "8b-v1.5-q4_K_S", "8b-v1.5-q4_K_M", "8b-v1.5-q5_K_S", "8b-v1.5-q5_K_M", "8b-v1.5-q6_K", "8b-v1.5-fp16"]}, "wizard-vicuna": {"description": "Wizard Vicuna is a 13B parameter model based on Llama 2 trained by MelodysDreamj.", "tags": ["latest", "13b", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16"]}, "snowflake-arctic-embed": {"description": "A suite of text embedding models by Snowflake, optimized for performance.", "tags": ["latest", "335m", "137m", "110m", "33m", "22m", "l", "m", "s", "xs", "335m-l-fp16", "137m-m-long-fp16", "110m-m-fp16", "33m-s-fp16", "22m-xs-fp16", "m-long"]}, "llava-llama3": {"description": "A LLaVA model fine-tuned from Llama 3 Instruct with better scores in several benchmarks.", "tags": ["latest", "8b", "8b-v1.1-q4_0", "8b-v1.1-fp16"]}, "goliath": {"description": "A language model created by combining two fine-tuned Llama 2 70B models into one.", "tags": ["latest", "120b-q4_0", "120b-q4_1", "120b-q5_0", "120b-q5_1", "120b-q8_0", "120b-q2_K", "120b-q3_K_S", "120b-q3_K_M", "120b-q3_K_L", "120b-q4_K_S", "120b-q4_K_M", "120b-q5_K_S", "120b-q5_K_M", "120b-q6_K", "120b-fp16"]}, "open-orca-platypus2": {"description": "Merge of the Open Orca OpenChat model and the Garage-bAInd Platypus 2 model. Designed for chat and code generation.", "tags": ["latest", "13b", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16"]}, "moondream": {"description": "moondream2 is a small vision language model designed to run efficiently on edge devices.", "tags": ["latest", "1.8b", "v2", "1.8b-v2-q4_0", "1.8b-v2-q4_1", "1.8b-v2-q5_0", "1.8b-v2-q5_1", "1.8b-v2-q8_0", "1.8b-v2-q2_K", "1.8b-v2-q3_K_S", "1.8b-v2-q3_K_M", "1.8b-v2-q3_K_L", "1.8b-v2-q4_K_S", "1.8b-v2-q4_K_M", "1.8b-v2-q5_K_S", "1.8b-v2-q5_K_M", "1.8b-v2-q6_K", "1.8b-v2-fp16", "1.8b-v2-moondream2-text-model-f16"]}, "duckdb-nsql": {"description": "7B parameter text-to-SQL model made by MotherDuck and Numbers Station.", "tags": ["latest", "7b", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "notux": {"description": "A top-performing mixture of experts model, fine-tuned with high-quality data.", "tags": ["latest", "8x7b", "8x7b-v1", "8x7b-v1-q4_0", "8x7b-v1-q4_1", "8x7b-v1-q5_0", "8x7b-v1-q5_1", "8x7b-v1-q8_0", "8x7b-v1-q2_K", "8x7b-v1-q3_K_S", "8x7b-v1-q3_K_M", "8x7b-v1-q3_K_L", "8x7b-v1-q4_K_S", "8x7b-v1-q4_K_M", "8x7b-v1-q5_K_S", "8x7b-v1-q5_K_M", "8x7b-v1-q6_K", "8x7b-v1-fp16"]}, "megadolphin": {"description": "MegaDolphin-2.2-120b is a transformation of Dolphin-2.2-70b created by interleaving the model with itself.", "tags": ["latest", "120b", "v2.2", "120b-v2.2", "120b-v2.2-q4_0", "120b-v2.2-q4_1", "120b-v2.2-q5_0", "120b-v2.2-q5_1", "120b-v2.2-q8_0", "120b-v2.2-q2_K", "120b-v2.2-q3_K_S", "120b-v2.2-q3_K_M", "120b-v2.2-q3_K_L", "120b-v2.2-q4_K_S", "120b-v2.2-q4_K_M", "120b-v2.2-q5_K_S", "120b-v2.2-q5_K_M", "120b-v2.2-q6_K", "120b-v2.2-fp16"]}, "notus": {"description": "A 7B chat model fine-tuned with high-quality data and based on Zephyr.", "tags": ["latest", "7b", "7b-v1", "7b-v1-q4_0", "7b-v1-q4_1", "7b-v1-q5_0", "7b-v1-q5_1", "7b-v1-q8_0", "7b-v1-q2_K", "7b-v1-q3_K_S", "7b-v1-q3_K_M", "7b-v1-q3_K_L", "7b-v1-q4_K_S", "7b-v1-q4_K_M", "7b-v1-q5_K_S", "7b-v1-q5_K_M", "7b-v1-q6_K", "7b-v1-fp16"]}, "alfred": {"description": "A robust conversational model designed to be used for both chat and instruct use cases.", "tags": ["latest", "40b", "40b-1023-q4_0", "40b-1023-q4_1", "40b-1023-q5_0", "40b-1023-q5_1", "40b-1023-q8_0"]}, "llava-phi3": {"description": "A new small LLaVA model fine-tuned from Phi 3 Mini.", "tags": ["latest", "3.8b", "3.8b-mini-q4_0", "3.8b-mini-fp16"]}, "falcon2": {"description": "Falcon2 is an 11B parameters causal decoder-only model built by TII and trained over 5T tokens.", "tags": ["latest", "11b", "11b-q4_0", "11b-q4_1", "11b-q5_0", "11b-q5_1", "11b-q8_0", "11b-q2_K", "11b-q3_K_S", "11b-q3_K_M", "11b-q3_K_L", "11b-q4_K_S", "11b-q4_K_M", "11b-q5_K_S", "11b-q5_K_M", "11b-q6_K", "11b-fp16"]}}
+available_models = {"llama3": {"url": "https://ollama.com/library/llama3", "tags": ["latest", "70b", "8b", "instruct", "text", "70b-instruct", "70b-text", "70b-instruct-q4_0", "70b-instruct-q4_1", "70b-instruct-q5_0", "70b-instruct-q5_1", "70b-instruct-q8_0", "70b-instruct-q2_K", "70b-instruct-q3_K_S", "70b-instruct-q3_K_M", "70b-instruct-q3_K_L", "70b-instruct-q4_K_S", "70b-instruct-q4_K_M", "70b-instruct-q5_K_S", "70b-instruct-q5_K_M", "70b-instruct-q6_K", "70b-instruct-fp16", "70b-text-q4_0", "70b-text-q4_1", "70b-text-q5_0", "70b-text-q5_1", "70b-text-q8_0", "70b-text-q2_K", "70b-text-q3_K_S", "70b-text-q3_K_M", "70b-text-q3_K_L", "70b-text-q4_K_S", "70b-text-q4_K_M", "70b-text-q5_K_S", "70b-text-q5_K_M", "70b-text-q6_K", "70b-text-fp16", "8b-text", "8b-instruct-q4_0", "8b-instruct-q4_1", "8b-instruct-q5_0", "8b-instruct-q5_1", "8b-instruct-q8_0", "8b-instruct-q2_K", "8b-instruct-q3_K_S", "8b-instruct-q3_K_M", "8b-instruct-q3_K_L", "8b-instruct-q4_K_S", "8b-instruct-q4_K_M", "8b-instruct-q5_K_S", "8b-instruct-q5_K_M", "8b-instruct-q6_K", "8b-instruct-fp16", "8b-text-q4_0", "8b-text-q4_1", "8b-text-q5_0", "8b-text-q5_1", "8b-text-q8_0", "8b-text-q2_K", "8b-text-q3_K_S", "8b-text-q3_K_M", "8b-text-q3_K_L", "8b-text-q4_K_S", "8b-text-q4_K_M", "8b-text-q5_K_S", "8b-text-q6_K", "8b-text-fp16"]}, "phi3": {"url": "https://ollama.com/library/phi3", "tags": ["latest", "3.8b", "instruct", "mini", "3.8b-mini-instruct-4k-q4_K_M", "3.8b-mini-instruct-4k-fp16"]}, "wizardlm2": {"url": "https://ollama.com/library/wizardlm2", "tags": ["latest", "8x22b", "7b", "8x22b-q4_0", "8x22b-q8_0", "8x22b-q2_K", "8x22b-fp16", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "mistral": {"url": "https://ollama.com/library/mistral", "tags": ["latest", "7b", "instruct", "text", "v0.1", "v0.2", "7b-instruct", "7b-text", "7b-instruct-q4_0", "7b-instruct-q4_1", "7b-instruct-q5_0", "7b-instruct-q5_1", "7b-instruct-q8_0", "7b-instruct-q2_K", "7b-instruct-q3_K_S", "7b-instruct-q3_K_M", "7b-instruct-q3_K_L", "7b-instruct-q4_K_S", "7b-instruct-q4_K_M", "7b-instruct-q5_K_S", "7b-instruct-q5_K_M", "7b-instruct-q6_K", "7b-instruct-fp16", "7b-text-q4_0", "7b-text-q4_1", "7b-text-q5_0", "7b-text-q5_1", "7b-text-q8_0", "7b-text-q2_K", "7b-text-q3_K_S", "7b-text-q3_K_M", "7b-text-q3_K_L", "7b-text-q4_K_S", "7b-text-q4_K_M", "7b-text-q5_K_S", "7b-text-q5_K_M", "7b-text-q6_K", "7b-text-fp16", "7b-instruct-v0.2-q4_0", "7b-instruct-v0.2-q4_1", "7b-instruct-v0.2-q5_0", "7b-instruct-v0.2-q5_1", "7b-instruct-v0.2-q8_0", "7b-instruct-v0.2-q2_K", "7b-instruct-v0.2-q3_K_S", "7b-instruct-v0.2-q3_K_M", "7b-instruct-v0.2-q3_K_L", "7b-instruct-v0.2-q4_K_S", "7b-instruct-v0.2-q4_K_M", "7b-instruct-v0.2-q5_K_S", "7b-instruct-v0.2-q5_K_M", "7b-instruct-v0.2-q6_K", "7b-instruct-v0.2-fp16", "7b-text-v0.2-q4_0", "7b-text-v0.2-q4_1", "7b-text-v0.2-q5_0", "7b-text-v0.2-q5_1", "7b-text-v0.2-q8_0", "7b-text-v0.2-q2_K", "7b-text-v0.2-q3_K_S", "7b-text-v0.2-q3_K_M", "7b-text-v0.2-q3_K_L", "7b-text-v0.2-q4_K_S", "7b-text-v0.2-q4_K_M", "7b-text-v0.2-q5_K_S", "7b-text-v0.2-q5_K_M", "7b-text-v0.2-q6_K", "7b-text-v0.2-fp16"]}, "gemma": {"url": "https://ollama.com/library/gemma", "tags": ["latest", "7b", "2b", "instruct", "text", "v1.1", "7b-instruct", "7b-text", "7b-v1.1", "7b-instruct-q4_0", "7b-instruct-q4_1", "7b-instruct-q5_0", "7b-instruct-q5_1", "7b-instruct-q8_0", "7b-instruct-q2_K", "7b-instruct-q3_K_S", "7b-instruct-q3_K_M", "7b-instruct-q3_K_L", "7b-instruct-q4_K_S", "7b-instruct-q4_K_M", "7b-instruct-q5_K_S", "7b-instruct-q5_K_M", "7b-instruct-q6_K", "7b-instruct-fp16", "7b-text-q4_0", "7b-text-q4_1", "7b-text-q5_0", "7b-text-q5_1", "7b-text-q8_0", "7b-text-q2_K", "7b-text-q3_K_S", "7b-text-q3_K_M", "7b-text-q3_K_L", "7b-text-q4_K_S", "7b-text-q4_K_M", "7b-text-q5_K_S", "7b-text-q5_K_M", "7b-text-q6_K", "7b-text-fp16", "7b-instruct-v1.1-q4_0", 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"70b-q4_K_S", "70b-q4_K_M", "70b-q5_K_S", "70b-q5_K_M", "70b-q6_K", "70b-fp16", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "wizardlm": {"url": "https://ollama.com/library/wizardlm", "tags": ["70b-llama2-q4_0", "70b-llama2-q4_1", "70b-llama2-q5_0", "70b-llama2-q8_0", "70b-llama2-q2_K", "70b-llama2-q3_K_S", "70b-llama2-q3_K_M", "70b-llama2-q3_K_L", "70b-llama2-q4_K_S", "70b-llama2-q4_K_M", "70b-llama2-q5_K_S", "70b-llama2-q5_K_M", "70b-llama2-q6_K", "30b-q4_0", "30b-q4_1", "30b-q5_0", "30b-q5_1", "30b-q8_0", "30b-q2_K", "30b-q3_K_S", "30b-q3_K_M", "30b-q3_K_L", "30b-q4_K_S", "30b-q4_K_M", "30b-q5_K_S", "30b-q5_K_M", "30b-q6_K", "30b-fp16", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16", "13b-llama2-q4_0", "13b-llama2-q4_1", "13b-llama2-q5_0", "13b-llama2-q5_1", "13b-llama2-q8_0", "13b-llama2-q2_K", "13b-llama2-q3_K_S", "13b-llama2-q3_K_M", "13b-llama2-q3_K_L", "13b-llama2-q4_K_S", "13b-llama2-q4_K_M", "13b-llama2-q5_K_S", "13b-llama2-q5_K_M", "13b-llama2-q6_K", "13b-llama2-fp16", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "codeup": {"url": "https://ollama.com/library/codeup", "tags": ["latest", "13b", "13b-llama2", "13b-llama2-chat", "13b-llama2-chat-q4_0", "13b-llama2-chat-q4_1", "13b-llama2-chat-q5_0", "13b-llama2-chat-q5_1", "13b-llama2-chat-q8_0", "13b-llama2-chat-q2_K", "13b-llama2-chat-q3_K_S", "13b-llama2-chat-q3_K_M", "13b-llama2-chat-q3_K_L", "13b-llama2-chat-q4_K_S", "13b-llama2-chat-q4_K_M", "13b-llama2-chat-q5_K_S", "13b-llama2-chat-q5_K_M", "13b-llama2-chat-q6_K", "13b-llama2-chat-fp16"]}, "yarn-mistral": {"url": "https://ollama.com/library/yarn-mistral", "tags": ["latest", "7b", "7b-128k", "7b-64k", "7b-128k-q4_0", "7b-128k-q4_1", "7b-128k-q5_0", "7b-128k-q5_1", "7b-128k-q8_0", "7b-128k-q2_K", "7b-128k-q3_K_S", "7b-128k-q3_K_M", "7b-128k-q3_K_L", "7b-128k-q4_K_S", "7b-128k-q4_K_M", "7b-128k-q5_K_S", "7b-128k-q5_K_M", "7b-128k-q6_K", "7b-128k-fp16", "7b-64k-q4_0", "7b-64k-q4_1", "7b-64k-q5_0", "7b-64k-q5_1", "7b-64k-q8_0", "7b-64k-q2_K", "7b-64k-q3_K_S", "7b-64k-q3_K_M", "7b-64k-q3_K_L", "7b-64k-q4_K_S", "7b-64k-q4_K_M", "7b-64k-q5_K_S", "7b-64k-q5_K_M", "7b-64k-q6_K"]}, "everythinglm": {"url": "https://ollama.com/library/everythinglm", "tags": ["latest", "13b", "13b-16k", "13b-16k-q4_0", "13b-16k-q4_1", "13b-16k-q5_0", "13b-16k-q5_1", "13b-16k-q8_0", "13b-16k-q2_K", "13b-16k-q3_K_S", "13b-16k-q3_K_M", "13b-16k-q3_K_L", "13b-16k-q4_K_S", "13b-16k-q4_K_M", "13b-16k-q5_K_S", "13b-16k-q5_K_M", "13b-16k-q6_K", "13b-16k-fp16"]}, "meditron": {"url": "https://ollama.com/library/meditron", "tags": ["latest", "70b", "7b", "70b-q4_0", "70b-q4_1", "70b-q5_1", "70b-q4_K_S", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "llama-pro": {"url": "https://ollama.com/library/llama-pro", "tags": ["latest", "instruct", "text", "8b-instruct-q4_0", "8b-instruct-q4_1", "8b-instruct-q5_0", "8b-instruct-q5_1", "8b-instruct-q8_0", "8b-instruct-q2_K", "8b-instruct-q3_K_S", "8b-instruct-q3_K_M", "8b-instruct-q3_K_L", "8b-instruct-q4_K_S", "8b-instruct-q4_K_M", "8b-instruct-q5_K_S", "8b-instruct-q5_K_M", "8b-instruct-q6_K", "8b-instruct-fp16", "8b-text-q4_0", "8b-text-q4_1", "8b-text-q5_0", "8b-text-q5_1", "8b-text-q8_0", "8b-text-q2_K", "8b-text-q3_K_S", "8b-text-q3_K_M", "8b-text-q3_K_L", "8b-text-q4_K_S", "8b-text-q4_K_M", "8b-text-q5_K_S", "8b-text-q5_K_M", "8b-text-q6_K", "8b-text-fp16"]}, "magicoder": {"url": "https://ollama.com/library/magicoder", "tags": ["latest", "7b", "7b-s-cl", "7b-s-cl-q4_0", "7b-s-cl-q4_1", "7b-s-cl-q5_0", "7b-s-cl-q5_1", "7b-s-cl-q8_0", "7b-s-cl-q2_K", "7b-s-cl-q3_K_S", "7b-s-cl-q3_K_M", "7b-s-cl-q3_K_L", "7b-s-cl-q4_K_S", "7b-s-cl-q4_K_M", "7b-s-cl-q5_K_S", "7b-s-cl-q5_K_M", "7b-s-cl-q6_K", "7b-s-cl-fp16"]}, "stablelm-zephyr": {"url": "https://ollama.com/library/stablelm-zephyr", "tags": ["latest", "3b", "3b-q4_0", "3b-q4_1", "3b-q5_0", "3b-q5_1", "3b-q8_0", "3b-q2_K", "3b-q3_K_S", "3b-q3_K_M", "3b-q3_K_L", "3b-q4_K_S", "3b-q4_K_M", "3b-q5_K_S", "3b-q5_K_M", "3b-q6_K", "3b-fp16"]}, "nexusraven": {"url": "https://ollama.com/library/nexusraven", "tags": ["latest", "13b", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16", "13b-v2-q4_0", "13b-v2-q4_1", "13b-v2-q5_0", "13b-v2-q5_1", "13b-v2-q8_0", "13b-v2-q2_K", "13b-v2-q3_K_S", "13b-v2-q3_K_M", "13b-v2-q3_K_L", "13b-v2-q4_K_S", "13b-v2-q4_K_M", "13b-v2-q5_K_S", "13b-v2-q5_K_M", "13b-v2-q6_K", "13b-v2-fp16"]}, "codebooga": {"url": "https://ollama.com/library/codebooga", "tags": ["latest", "34b", "34b-v0.1-q4_0", "34b-v0.1-q4_1", "34b-v0.1-q5_0", "34b-v0.1-q5_1", "34b-v0.1-q8_0", "34b-v0.1-q2_K", "34b-v0.1-q3_K_S", "34b-v0.1-q3_K_M", "34b-v0.1-q3_K_L", "34b-v0.1-q4_K_M", "34b-v0.1-q5_K_S", "34b-v0.1-q5_K_M", "34b-v0.1-q6_K", "34b-v0.1-fp16"]}, "llama3-chatqa": {"url": "https://ollama.com/library/llama3-chatqa", "tags": ["latest", "70b", "8b", "70b-v1.5", "70b-v1.5-q4_0", "70b-v1.5-q4_1", "70b-v1.5-q5_0", "70b-v1.5-q5_1", "70b-v1.5-q8_0", "70b-v1.5-q2_K", "70b-v1.5-q3_K_S", "70b-v1.5-q3_K_M", "70b-v1.5-q3_K_L", "70b-v1.5-q4_K_S", "70b-v1.5-q4_K_M", "70b-v1.5-q5_K_S", "70b-v1.5-q5_K_M", "70b-v1.5-q6_K", "70b-v1.5-fp16", "8b-v1.5", "8b-v1.5-q4_0", "8b-v1.5-q4_1", "8b-v1.5-q5_0", "8b-v1.5-q5_1", "8b-v1.5-q8_0", "8b-v1.5-q2_K", "8b-v1.5-q3_K_S", "8b-v1.5-q3_K_M", "8b-v1.5-q3_K_L", "8b-v1.5-q4_K_S", "8b-v1.5-q4_K_M", "8b-v1.5-q5_K_S", "8b-v1.5-q5_K_M", "8b-v1.5-q6_K", "8b-v1.5-fp16"]}, "mistrallite": {"url": "https://ollama.com/library/mistrallite", "tags": ["latest", "7b", "7b-v0.1-q4_0", "7b-v0.1-q4_1", "7b-v0.1-q5_0", "7b-v0.1-q5_1", "7b-v0.1-q8_0", "7b-v0.1-q2_K", "7b-v0.1-q3_K_S", "7b-v0.1-q3_K_M", "7b-v0.1-q3_K_L", "7b-v0.1-q4_K_S", "7b-v0.1-q4_K_M", "7b-v0.1-q5_K_S", "7b-v0.1-q5_K_M", "7b-v0.1-q6_K", "7b-v0.1-fp16"]}, "wizard-vicuna": {"url": "https://ollama.com/library/wizard-vicuna", "tags": ["latest", "13b", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16"]}, "llava-llama3": {"url": "https://ollama.com/library/llava-llama3", "tags": ["latest", "8b", "8b-v1.1-q4_0", "8b-v1.1-fp16"]}, "snowflake-arctic-embed": {"url": "https://ollama.com/library/snowflake-arctic-embed", "tags": ["latest", "335m", "137m", "110m", "33m", "22m", "l", "m", "s", "xs", "335m-l-fp16", "137m-m-long-fp16", "110m-m-fp16", "33m-s-fp16", "22m-xs-fp16", "m-long"]}, "goliath": {"url": "https://ollama.com/library/goliath", "tags": ["latest", "120b-q4_0", "120b-q4_1", "120b-q5_0", "120b-q5_1", "120b-q8_0", "120b-q2_K", "120b-q3_K_S", "120b-q3_K_M", "120b-q3_K_L", "120b-q4_K_S", "120b-q4_K_M", "120b-q5_K_S", "120b-q5_K_M", "120b-q6_K", "120b-fp16"]}, "open-orca-platypus2": {"url": "https://ollama.com/library/open-orca-platypus2", "tags": ["latest", "13b", "13b-q4_0", "13b-q4_1", "13b-q5_0", "13b-q5_1", "13b-q8_0", "13b-q2_K", "13b-q3_K_S", "13b-q3_K_M", "13b-q3_K_L", "13b-q4_K_S", "13b-q4_K_M", "13b-q5_K_S", "13b-q5_K_M", "13b-q6_K", "13b-fp16"]}, "moondream": {"url": "https://ollama.com/library/moondream", "tags": ["latest", "1.8b", "v2", "1.8b-v2-q4_0", "1.8b-v2-q4_1", "1.8b-v2-q5_0", "1.8b-v2-q5_1", "1.8b-v2-q8_0", "1.8b-v2-q2_K", "1.8b-v2-q3_K_S", "1.8b-v2-q3_K_M", "1.8b-v2-q3_K_L", "1.8b-v2-q4_K_S", "1.8b-v2-q4_K_M", "1.8b-v2-q5_K_S", "1.8b-v2-q5_K_M", "1.8b-v2-q6_K", "1.8b-v2-fp16"]}, "duckdb-nsql": {"url": "https://ollama.com/library/duckdb-nsql", "tags": ["latest", "7b", "7b-q4_0", "7b-q4_1", "7b-q5_0", "7b-q5_1", "7b-q8_0", "7b-q2_K", "7b-q3_K_S", "7b-q3_K_M", "7b-q3_K_L", "7b-q4_K_S", "7b-q4_K_M", "7b-q5_K_S", "7b-q5_K_M", "7b-q6_K", "7b-fp16"]}, "notux": {"url": "https://ollama.com/library/notux", "tags": ["latest", "8x7b", "8x7b-v1", "8x7b-v1-q4_0", "8x7b-v1-q4_1", "8x7b-v1-q5_0", "8x7b-v1-q5_1", "8x7b-v1-q8_0", "8x7b-v1-q2_K", "8x7b-v1-q3_K_S", "8x7b-v1-q3_K_M", "8x7b-v1-q3_K_L", "8x7b-v1-q4_K_S", "8x7b-v1-q4_K_M", "8x7b-v1-q5_K_S", "8x7b-v1-q5_K_M", "8x7b-v1-q6_K", "8x7b-v1-fp16"]}, "megadolphin": {"url": "https://ollama.com/library/megadolphin", "tags": ["latest", "120b", "v2.2", "120b-v2.2", "120b-v2.2-q4_0", "120b-v2.2-q4_1", "120b-v2.2-q5_0", "120b-v2.2-q5_1", "120b-v2.2-q8_0", "120b-v2.2-q2_K", "120b-v2.2-q3_K_S", "120b-v2.2-q3_K_M", "120b-v2.2-q3_K_L", "120b-v2.2-q4_K_S", "120b-v2.2-q4_K_M", "120b-v2.2-q5_K_S", "120b-v2.2-q5_K_M", "120b-v2.2-q6_K", "120b-v2.2-fp16"]}, "notus": {"url": "https://ollama.com/library/notus", "tags": ["latest", "7b", "7b-v1", "7b-v1-q4_0", "7b-v1-q4_1", "7b-v1-q5_0", "7b-v1-q5_1", "7b-v1-q8_0", "7b-v1-q2_K", "7b-v1-q3_K_S", "7b-v1-q3_K_M", "7b-v1-q3_K_L", "7b-v1-q4_K_S", "7b-v1-q4_K_M", "7b-v1-q5_K_S", "7b-v1-q5_K_M", "7b-v1-q6_K", "7b-v1-fp16"]}, "alfred": {"url": "https://ollama.com/library/alfred", "tags": ["latest", "40b", "40b-1023-q4_0", "40b-1023-q4_1", "40b-1023-q5_0", "40b-1023-q5_1", "40b-1023-q8_0"]}, "llava-phi3": {"url": "https://ollama.com/library/llava-phi3", "tags": ["latest", "3.8b", "3.8b-mini-q4_0", "3.8b-mini-fp16"]}, "falcon2": {"url": "https://ollama.com/library/falcon2", "tags": ["latest", "11b", "11b-q4_0", "11b-q4_1", "11b-q5_0", "11b-q5_1", "11b-q8_0", "11b-q2_K", "11b-q3_K_S", "11b-q3_K_M", "11b-q3_K_L", "11b-q4_K_S", "11b-q4_K_M", "11b-q5_K_S", "11b-q5_K_M", "11b-q6_K", "11b-fp16"]}}
diff --git a/src/window.py b/src/window.py
index 9d469c9..d0f3d03 100644
--- a/src/window.py
+++ b/src/window.py
@@ -21,7 +21,7 @@ import gi
 gi.require_version('GtkSource', '5')
 gi.require_version('GdkPixbuf', '2.0')
 from gi.repository import Adw, Gtk, Gdk, GLib, GtkSource, Gio, GdkPixbuf
-import json, requests, threading, os, re, base64, sys, gettext, locale
+import json, requests, threading, os, re, base64, sys, gettext, locale, webbrowser
 from io import BytesIO
 from PIL import Image
 from datetime import datetime
@@ -511,17 +511,24 @@ class AlpacaWindow(Adw.ApplicationWindow):
         self.available_model_list_box.remove_all()
         for name, model_info in available_models.items():
             model = Adw.ActionRow(
-                title = name,
-                subtitle = model_info['description'],
+                title = name
             )
-            button = Gtk.Button(
+            link_button = Gtk.Button(
+                icon_name = "web-browser-symbolic",
+                vexpand = False,
+                valign = 3,
+                css_classes = ["success"]
+            )
+            pull_button = Gtk.Button(
                 icon_name = "folder-download-symbolic",
                 vexpand = False,
                 valign = 3,
                 css_classes = ["accent"]
             )
-            button.connect("clicked", lambda button=button, model_name=name: self.model_pull_button_activate(model_name))
-            model.add_suffix(button)
+            link_button.connect("clicked", lambda button=link_button, link=model_info["url"]: webbrowser.open(link))
+            pull_button.connect("clicked", lambda button=pull_button, model_name=name: self.model_pull_button_activate(model_name))
+            model.add_suffix(link_button)
+            model.add_suffix(pull_button)
             self.available_model_list_box.append(model)
 
     def manage_models_button_activate(self, button=None):