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internlm2_5-20b-chat-GGUF

Original Model

internlm/internlm2_5-20b-chat

Run with LlamaEdge

  • LlamaEdge version: v0.13.0 and above

  • Prompt template

    • Prompt type: chatml

    • Prompt string

      <|im_start|>system
      {system_message}<|im_end|>
      <|im_start|>user
      {prompt}<|im_end|>
      <|im_start|>assistant
      
  • Context size: 32000

  • Run as LlamaEdge service

    • Chat

      wasmedge --dir .:. --nn-preload default:GGML:AUTO:internlm2_5-20b-chat-Q5_K_M.gguf \
        llama-api-server.wasm \
        --prompt-template chatml \
        --ctx-size 32000 \
        --model-name internlm2_5-20b-chat
      
    • Tool use

      wasmedge --dir .:. --nn-preload default:GGML:AUTO:internlm2_5-20b-chat-Q5_K_M.gguf \
        llama-api-server.wasm \
        --prompt-template internlm-2-tool \
        --ctx-size 32000 \
        --model-name internlm2_5-20b-chat
      
  • Run as LlamaEdge command app

    wasmedge --dir .:. \
      --nn-preload default:GGML:AUTO:internlm2_5-20b-chat-Q5_K_M.gguf \
      llama-chat.wasm \
      --prompt-template chatml \
      --ctx-size 32000
    

Quantized GGUF Models

Name Quant method Bits Size Use case
internlm2_5-20b-chat-Q2_K.gguf Q2_K 2 7.55 GB smallest, significant quality loss - not recommended for most purposes
internlm2_5-20b-chat-Q3_K_L.gguf Q3_K_L 3 10.6 GB small, substantial quality loss
internlm2_5-20b-chat-Q3_K_M.gguf Q3_K_M 3 9.72 GB very small, high quality loss
internlm2_5-20b-chat-Q3_K_S.gguf Q3_K_S 3 8.76 GB very small, high quality loss
internlm2_5-20b-chat-Q4_0.gguf Q4_0 4 11.3 GB legacy; small, very high quality loss - prefer using Q3_K_M
internlm2_5-20b-chat-Q4_K_M.gguf Q4_K_M 4 12.0 GB medium, balanced quality - recommended
internlm2_5-20b-chat-Q4_K_S.gguf Q4_K_S 4 11.4 GB small, greater quality loss
internlm2_5-20b-chat-Q5_0.gguf Q5_0 5 13.7 GB legacy; medium, balanced quality - prefer using Q4_K_M
internlm2_5-20b-chat-Q5_K_M.gguf Q5_K_M 5 14.1 GB large, very low quality loss - recommended
internlm2_5-20b-chat-Q5_K_S.gguf Q5_K_S 5 13.7 GB large, low quality loss - recommended
internlm2_5-20b-chat-Q6_K.gguf Q6_K 6 16.3 GB very large, extremely low quality loss
internlm2_5-20b-chat-Q8_0.gguf Q8_0 8 21.1 GB very large, extremely low quality loss - not recommended
internlm2_5-20b-chat-f16.gguf f16 16 39.7 GB

Quantized with llama.cpp b3499

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GGUF
Model size
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Architecture
internlm2

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Inference Examples
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