Edit model card

Yi-1.5-6B-Chat-GGUF

Original Model

01-ai/Yi-1.5-6B-Chat

Run with LlamaEdge

  • LlamaEdge version: v0.10.0 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
      
    • Reverse prompt: <|im_end|>

  • Context size: 4096

  • Run as LlamaEdge service

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Yi-1.5-6B-Chat-Q5_K_M.gguf \
      llama-api-server.wasm \
      --prompt-template chatml \
      --reverse-prompt "<|im_end|>" \
      --ctx-size 4096 \
      --model-name Yi-1.5-6B-Chat
    
  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Yi-1.5-6B-Chat-Q5_K_M.gguf \
      llama-chat.wasm \
      --prompt-template chatml \
      --reverse-prompt "<|im_end|>" \
      --ctx-size 4096
    

Quantized GGUF Models

Name Quant method Bits Size Use case
Yi-1.5-6B-Chat-Q2_K.gguf Q2_K 2 2.34 GB smallest, significant quality loss - not recommended for most purposes
Yi-1.5-6B-Chat-Q3_K_L.gguf Q3_K_L 3 3.24 GB small, substantial quality loss
Yi-1.5-6B-Chat-Q3_K_M.gguf Q3_K_M 3 2.99 GB very small, high quality loss
Yi-1.5-6B-Chat-Q3_K_S.gguf Q3_K_S 3 2.71 GB very small, high quality loss
Yi-1.5-6B-Chat-Q4_0.gguf Q4_0 4 3.48 GB legacy; small, very high quality loss - prefer using Q3_K_M
Yi-1.5-6B-Chat-Q4_K_M.gguf Q4_K_M 4 3.67 GB medium, balanced quality - recommended
Yi-1.5-6B-Chat-Q4_K_S.gguf Q4_K_S 4 3.5 GB small, greater quality loss
Yi-1.5-6B-Chat-Q5_0.gguf Q5_0 5 4.2 GB legacy; medium, balanced quality - prefer using Q4_K_M
Yi-1.5-6B-Chat-Q5_K_M.gguf Q5_K_M 5 4.3 GB large, very low quality loss - recommended
Yi-1.5-6B-Chat-Q5_K_S.gguf Q5_K_S 5 4.2 GB large, low quality loss - recommended
Yi-1.5-6B-Chat-Q6_K.gguf Q6_K 6 4.97 GB very large, extremely low quality loss
Yi-1.5-6B-Chat-Q8_0.gguf Q8_0 8 6.44 GB very large, extremely low quality loss - not recommended
Yi-1.5-6B-Chat-f16.gguf f16 16 12.1 GB

Quantized with llama.cpp b3135

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

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