mixtral-instruct-v0.1

• Context Length: 32768

• Model Name: mixtral-instruct-v0.1

• Languages: en, fr, it, de, es

• Abilities: chat

• Description: Mistral-8x7B-Instruct is a fine-tuned version of the Mistral-8x7B LLM, specializing in chatting.

Specifications

Model Spec 1 (pytorch, 46_7 Billion)

• Model Format: pytorch

• Model Size (in billions): 46_7

• Quantizations: 4-bit, 8-bit, none

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

Model Spec 2 (awq, 46_7 Billion)

• Model Format: awq

• Model Size (in billions): 46_7

• Quantizations: Int4

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

• 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-name mixtral-instruct-v0.1 --size-in-billions 46_7 --model-format awq --quantization ${quantization}

Model Spec 3 (gptq, 46_7 Billion)

• Model Format: gptq

• Model Size (in billions): 46_7

• Quantizations: Int4

• Model ID: TheBloke/Mixtral-8x7B-Instruct-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-name mixtral-instruct-v0.1 --size-in-billions 46_7 --model-format gptq --quantization ${quantization}

Model Spec 4 (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

• Model ID: TheBloke/Mixtral-8x7B-Instruct-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-name mixtral-instruct-v0.1 --size-in-billions 46_7 --model-format ggufv2 --quantization ${quantization}