Edit model card

Qwen2-7B-Instruct-GGUF

Original Model

Qwen/Qwen2-7B-Instruct

Run with LlamaEdge

  • LlamaEdge version: v0.11.2

  • 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:Qwen2-7B-Instruct-Q5_K_M.gguf \
      llama-api-server.wasm \
      --model-name Qwen2-7B-Instruct \
      --prompt-template chatml \
      --ctx-size 131072
    
  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Qwen2-7B-Instruct-Q5_K_M.gguf \
      llama-chat.wasm \
      --prompt-template chatml \
      --ctx-size 131072
    

Quantized GGUF Models

Name Quant method Bits Size Use case
Qwen2-7B-Instruct-Q2_K.gguf Q2_K 2 3.02 GB smallest, significant quality loss - not recommended for most purposes
Qwen2-7B-Instruct-Q3_K_L.gguf Q3_K_L 3 4.09 GB small, substantial quality loss
Qwen2-7B-Instruct-Q3_K_M.gguf Q3_K_M 3 3.81 GB very small, high quality loss
Qwen2-7B-Instruct-Q3_K_S.gguf Q3_K_S 3 3.49 GB very small, high quality loss
Qwen2-7B-Instruct-Q4_0.gguf Q4_0 4 4.43 GB legacy; small, very high quality loss - prefer using Q3_K_M
Qwen2-7B-Instruct-Q4_K_M.gguf Q4_K_M 4 4.68 GB medium, balanced quality - recommended
Qwen2-7B-Instruct-Q4_K_S.gguf Q4_K_S 4 4.46 GB small, greater quality loss
Qwen2-7B-Instruct-Q5_0.gguf Q5_0 5 5.32 GB legacy; medium, balanced quality - prefer using Q4_K_M
Qwen2-7B-Instruct-Q5_K_M.gguf Q5_K_M 5 5.44 GB large, very low quality loss - recommended
Qwen2-7B-Instruct-Q5_K_S.gguf Q5_K_S 5 5.32 GB large, low quality loss - recommended
Qwen2-7B-Instruct-Q6_K.gguf Q6_K 6 6.25 GB very large, extremely low quality loss
Qwen2-7B-Instruct-Q8_0.gguf Q8_0 8 8.21 GB very large, extremely low quality loss - not recommended
Qwen2-7B-Instruct-f16.gguf f16 16 15.2 GB

Quantized with llama.cpp b3705

Downloads last month
1,805
GGUF
Model size
7.62B params
Architecture
qwen2
Inference API
This model can be loaded on Inference API (serverless).

Quantized from