mixtral-v0.1#

  • Context Length: 32768

  • Model Name: mixtral-v0.1

  • Languages: en, fr, it, de, es

  • Abilities: generate

  • Description: The Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts.

Specifications#

Model Spec 1 (pytorch, 46_7 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 46_7

  • Quantizations: 4-bit, 8-bit, none

  • Engines: Transformers, SGLang (vLLM and SGLang only available for quantization none)

  • Model ID: mistralai/Mixtral-8x7B-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 mixtral-v0.1 --size-in-billions 46_7 --model-format pytorch --quantization ${quantization}

Model Spec 2 (gptq, 46_7 Billion)#

  • Model Format: gptq

  • Model Size (in billions): 46_7

  • Quantizations: Int4

  • Engines: Transformers, SGLang

  • Model ID: TheBloke/Mixtral-8x7B-v0.1-GPTQ

  • Model Hubs: Hugging Face

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 mixtral-v0.1 --size-in-billions 46_7 --model-format gptq --quantization ${quantization}

Model Spec 3 (ggufv2, 46_7 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 46_7

  • Quantizations: Q2_K, Q3_K_M, Q4_0, Q4_K_M, Q5_0, Q5_K_M, Q6_K, Q8_0

  • Engines: llama.cpp

  • Model ID: TheBloke/Mixtral-8x7B-v0.1-GGUF

  • Model Hubs: Hugging Face

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 mixtral-v0.1 --size-in-billions 46_7 --model-format ggufv2 --quantization ${quantization}