mistral-instruct-v0.2

• Context Length: 8192

• Model Name: mistral-instruct-v0.2

• Languages: en

• Abilities: chat

• Description: The Mistral-7B-Instruct-v0.2 Large Language Model (LLM) is an improved instruct fine-tuned version of Mistral-7B-Instruct-v0.1.

Specifications

Model Spec 1 (pytorch, 7 Billion)

• Model Format: pytorch

• Model Size (in billions): 7

• Quantizations: 4-bit, 8-bit, none

• Model ID: mistralai/Mistral-7B-Instruct-v0.2

• 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 mistral-instruct-v0.2 --size-in-billions 7 --model-format pytorch --quantization ${quantization}

Model Spec 2 (gptq, 7 Billion)

• Model Format: gptq

• Model Size (in billions): 7

• Quantizations: Int4

• Model ID: TheBloke/Mistral-7B-Instruct-v0.2-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 mistral-instruct-v0.2 --size-in-billions 7 --model-format gptq --quantization ${quantization}

Model Spec 3 (awq, 7 Billion)

• Model Format: awq

• Model Size (in billions): 7

• Quantizations: Int4

• Model ID: TheBloke/Mistral-7B-Instruct-v0.2-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 mistral-instruct-v0.2 --size-in-billions 7 --model-format awq --quantization ${quantization}

Model Spec 4 (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

• Model ID: TheBloke/Mistral-7B-Instruct-v0.2-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-name mistral-instruct-v0.2 --size-in-billions 7 --model-format ggufv2 --quantization ${quantization}