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Qwen2-1.5B-Instruct-GGUF

Original Model

Qwen/Qwen2-1.5B-Instruct

Run with LlamaEdge

  • LlamaEdge version: v0.2.15 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

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Qwen2-1.5B-Instruct-Q5_K_M.gguf \
      llama-api-server.wasm \
      --model-name Qwen2-1.5B-Instruct \
      --prompt-template chatml \
      --ctx-size 32000
    
  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Qwen2-1.5B-Instruct-Q5_K_M.gguf \
      llama-chat.wasm \
      --prompt-template chatml \
      --ctx-size 32000
    

Quantized GGUF Models

Name Quant method Bits Size Use case
Qwen2-1.5B-Instruct-Q2_K.gguf Q2_K 2 676 MB smallest, significant quality loss - not recommended for most purposes
Qwen2-1.5B-Instruct-Q3_K_L.gguf Q3_K_L 3 880 MB small, substantial quality loss
Qwen2-1.5B-Instruct-Q3_K_M.gguf Q3_K_M 3 824 MB very small, high quality loss
Qwen2-1.5B-Instruct-Q3_K_S.gguf Q3_K_S 3 761 MB very small, high quality loss
Qwen2-1.5B-Instruct-Q4_0.gguf Q4_0 4 935 MB legacy; small, very high quality loss - prefer using Q3_K_M
Qwen2-1.5B-Instruct-Q4_K_M.gguf Q4_K_M 4 986 MB medium, balanced quality - recommended
Qwen2-1.5B-Instruct-Q4_K_S.gguf Q4_K_S 4 940 MB small, greater quality loss
Qwen2-1.5B-Instruct-Q5_0.gguf Q5_0 5 1.1 GB legacy; medium, balanced quality - prefer using Q4_K_M
Qwen2-1.5B-Instruct-Q5_K_M.gguf Q5_K_M 5 1.13 GB large, very low quality loss - recommended
Qwen2-1.5B-Instruct-Q5_K_S.gguf Q5_K_S 5 1.1 GB large, low quality loss - recommended
Qwen2-1.5B-Instruct-Q6_K.gguf Q6_K 6 1.27 GB very large, extremely low quality loss
Qwen2-1.5B-Instruct-Q8_0.gguf Q8_0 8 1.65 GB very large, extremely low quality loss - not recommended
Qwen2-1.5B-Instruct-f16.gguf f16 16 3.09 GB

Quantized with llama.cpp b3705

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GGUF
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qwen2

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