.. _models_llm_mistral-v0.1: ======================================== mistral-v0.1 ======================================== - **Context Length:** 8192 - **Model Name:** mistral-v0.1 - **Languages:** en - **Abilities:** generate - **Description:** Mistral-7B is a unmoderated Transformer based LLM claiming to outperform Llama2 on all benchmarks. Specifications ^^^^^^^^^^^^^^ Model Spec 1 (pytorch, 7 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 7 - **Quantizations:** 4-bit, 8-bit, none - **Engines**: vLLM, Transformers, SGLang (vLLM and SGLang only available for quantization none) - **Model ID:** mistralai/Mistral-7B-v0.1 - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name mistral-v0.1 --size-in-billions 7 --model-format pytorch --quantization ${quantization} Model Spec 2 (ggufv2, 7 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** ggufv2 - **Model Size (in billions):** 7 - **Quantizations:** Q2_K, Q3_K_S, Q3_K_M, Q3_K_L, Q4_0, Q4_K_S, Q4_K_M, Q5_0, Q5_K_S, Q5_K_M, Q6_K, Q8_0 - **Engines**: llama.cpp - **Model ID:** TheBloke/Mistral-7B-v0.1-GGUF - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name mistral-v0.1 --size-in-billions 7 --model-format ggufv2 --quantization ${quantization}