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Mistral-7B-Instruct-v0.3-GGUF

Original Model

mistralai/Mistral-7B-Instruct-v0.3

Run with LlamaEdge

  • LlamaEdge version: v0.11.2

  • Prompt template

    • Prompt type: mistral-instruct

    • Prompt string

      <s>[INST] {user_message_1} [/INST]{assistant_message_1}</s>[INST] {user_message_2} [/INST]{assistant_message_2}</s>
      
  • Context size: 32000

  • Run as LlamaEdge service

    • Chat

      wasmedge --dir .:. --nn-preload default:GGML:AUTO:Mistral-7B-Instruct-v0.3-Q5_K_M.gguf \
        llama-api-server.wasm \
        --prompt-template mistral-instruct \
        --ctx-size 32000 \
        --model-name Mistral-7B-Instruct-v0.3
      
    • Tool use

      wasmedge --dir .:. --nn-preload default:GGML:AUTO:Mistral-7B-Instruct-v0.3-Q5_K_M.gguf \
        llama-api-server.wasm \
        --prompt-template mistral-tool \
        --ctx-size 32000 \
        --model-name Mistral-7B-Instruct-v0.3
      
  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Mistral-7B-Instruct-v0.3-Q5_K_M.gguf \
      llama-chat.wasm \
      --prompt-template mistral-instruct \
      --ctx-size 32000
    

Quantized GGUF Models

Name Quant method Bits Size Use case
Mistral-7B-Instruct-v0.3-Q2_K.gguf Q2_K 2 2.72 GB smallest, significant quality loss - not recommended for most purposes
Mistral-7B-Instruct-v0.3-Q3_K_L.gguf Q3_K_L 3 3.83 GB small, substantial quality loss
Mistral-7B-Instruct-v0.3-Q3_K_M.gguf Q3_K_M 3 3.52 GB very small, high quality loss
Mistral-7B-Instruct-v0.3-Q3_K_S.gguf Q3_K_S 3 3.17 GB very small, high quality loss
Mistral-7B-Instruct-v0.3-Q4_0.gguf Q4_0 4 4.11 GB legacy; small, very high quality loss - prefer using Q3_K_M
Mistral-7B-Instruct-v0.3-Q4_K_M.gguf Q4_K_M 4 4.37 GB medium, balanced quality - recommended
Mistral-7B-Instruct-v0.3-Q4_K_S.gguf Q4_K_S 4 4.14 GB small, greater quality loss
Mistral-7B-Instruct-v0.3-Q5_0.gguf Q5_0 5 5 GB legacy; medium, balanced quality - prefer using Q4_K_M
Mistral-7B-Instruct-v0.3-Q5_K_M.gguf Q5_K_M 5 5.14 GB large, very low quality loss - recommended
Mistral-7B-Instruct-v0.3-Q5_K_S.gguf Q5_K_S 5 5 GB large, low quality loss - recommended
Mistral-7B-Instruct-v0.3-Q6_K.gguf Q6_K 6 5.95 GB very large, extremely low quality loss
Mistral-7B-Instruct-v0.3-Q8_0.gguf Q8_0 8 7.7 GB very large, extremely low quality loss - not recommended
Mistral-7B-Instruct-v0.3-f16.gguf f16 16 14.5 GB

Quantized with llama.cpp b3030.

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Inference Examples
Inference API (serverless) has been turned off for this model.

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