Edit model card

Qwen2.5-72B-Instruct-GGUF

Original Model

Qwen/Qwen2.5-72B-Instruct

Run with LlamaEdge

  • LlamaEdge version: v0.14.3

  • 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: 131072

  • Run as LlamaEdge service

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Qwen2.5-72B-Instruct-Q5_K_M.gguf \
      llama-api-server.wasm \
      --model-name Qwen2.5-72B-Instruct \
      --prompt-template chatml \
      --ctx-size 131072
    
  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Qwen2.5-72B-Instruct-Q5_K_M.gguf \
      llama-chat.wasm \
      --prompt-template chatml \
      --ctx-size 131072
    

Quantized GGUF Models

Name Quant method Bits Size Use case
Qwen2.5-72B-Instruct-Q2_K.gguf Q2_K 2 29.8 GB smallest, significant quality loss - not recommended for most purposes
Qwen2.5-72B-Instruct-Q3_K_L.gguf Q3_K_L 3 39.5 GB small, substantial quality loss
Qwen2.5-72B-Instruct-Q3_K_M.gguf Q3_K_M 3 37.7 GB very small, high quality loss
Qwen2.5-72B-Instruct-Q3_K_S.gguf Q3_K_S 3 34.5 GB very small, high quality loss
Qwen2.5-72B-Instruct-Q4_0.gguf Q4_0 4 41.2 GB legacy; small, very high quality loss - prefer using Q3_K_M
Qwen2.5-72B-Instruct-Q4_K_M.gguf Q4_K_M 4 47.4 GB medium, balanced quality - recommended
Qwen2.5-72B-Instruct-Q4_K_S.gguf Q4_K_S 4 43.9 GB small, greater quality loss
Qwen2.5-72B-Instruct-Q5_0-00001-of-00002.gguf Q5_0 5 30.0 GB legacy; medium, balanced quality - prefer using Q4_K_M
Qwen2.5-72B-Instruct-Q5_0-00002-of-00002.gguf Q5_0 5 20.2 GB legacy; medium, balanced quality - prefer using Q4_K_M
Qwen2.5-72B-Instruct-Q5_K_M-00001-of-00002.gguf Q5_K_M 5 29.9 GB large, very low quality loss - recommended
Qwen2.5-72B-Instruct-Q5_K_M-00002-of-00002.gguf Q5_K_M 5 24.6 GB large, very low quality loss - recommended
Qwen2.5-72B-Instruct-Q5_K_S-00001-of-00002.gguf Q5_K_S 5 29.9 GB large, low quality loss - recommended
Qwen2.5-72B-Instruct-Q5_K_S-00002-of-00002.gguf Q5_K_S 5 21.4 GB large, low quality loss - recommended
Qwen2.5-72B-Instruct-Q6_K-00001-of-00003.gguf Q6_K 6 29.8 GB very large, extremely low quality loss
Qwen2.5-72B-Instruct-Q6_K-00002-of-00003.gguf Q6_K 6 29.8 GB very large, extremely low quality loss
Qwen2.5-72B-Instruct-Q6_K-00003-of-00003.gguf Q6_K 6 4.66 GB very large, extremely low quality loss
Qwen2.5-72B-Instruct-Q8_0-00001-of-00003.gguf Q8_0 8 29.8 GB very large, extremely low quality loss - not recommended
Qwen2.5-72B-Instruct-Q8_0-00002-of-00003.gguf Q8_0 8 29.8 GB very large, extremely low quality loss - not recommended
Qwen2.5-72B-Instruct-Q8_0-00003-of-00003.gguf Q8_0 8 17.6 GB very large, extremely low quality loss - not recommended
Qwen2.5-72B-Instruct-f16-00001-of-00005.gguf f16 16 29.8 GB
Qwen2.5-72B-Instruct-f16-00002-of-00005.gguf f16 16 29.7 GB
Qwen2.5-72B-Instruct-f16-00003-of-00005.gguf f16 16 29.5 GB
Qwen2.5-72B-Instruct-f16-00004-of-00005.gguf f16 16 29.8 GB
Qwen2.5-72B-Instruct-f16-00005-of-00005.gguf f16 16 26.6 GB

Quantized with llama.cpp b3751

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GGUF
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qwen2

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Inference Examples
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