Edit model card

Nous-Hermes-2-Mixtral-8x7B-DPO-GGUF

Original Model

NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO

Run with LlamaEdge

  • LlamaEdge version: v0.2.8 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: 4096

  • Run as LlamaEdge service

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Nous-Hermes-2-Mixtral-8x7B-DPO-Q5_K_M.gguf llama-api-server.wasm -p chatml
    
  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Nous-Hermes-2-Mixtral-8x7B-DPO-Q5_K_M.gguf llama-chat.wasm -p chatml
    

Quantized GGUF Models

Name Quant method Bits Size Use case
Nous-Hermes-2-Mixtral-8x7B-DPO-Q2_K.gguf Q2_K 2 17.3 GB smallest, significant quality loss - not recommended for most purposes
Nous-Hermes-2-Mixtral-8x7B-DPO-Q3_K_L.gguf Q3_K_L 3 24.2 GB small, substantial quality loss
Nous-Hermes-2-Mixtral-8x7B-DPO-Q3_K_M.gguf Q3_K_M 3 22.5 GB very small, high quality loss
Nous-Hermes-2-Mixtral-8x7B-DPO-Q3_K_S.gguf Q3_K_S 3 20.4 GB very small, high quality loss
Nous-Hermes-2-Mixtral-8x7B-DPO-Q4_0.gguf Q4_0 4 26.4 GB legacy; small, very high quality loss - prefer using Q3_K_M
Nous-Hermes-2-Mixtral-8x7B-DPO-Q4_K_M.gguf Q4_K_M 4 28.4 GB medium, balanced quality - recommended
Nous-Hermes-2-Mixtral-8x7B-DPO-Q4_K_S.gguf Q4_K_S 4 26.7 GB small, greater quality loss
Nous-Hermes-2-Mixtral-8x7B-DPO-Q5_0.gguf Q5_0 5 32.2 GB legacy; medium, balanced quality - prefer using Q4_K_M
Nous-Hermes-2-Mixtral-8x7B-DPO-Q5_K_M.gguf Q5_K_M 5 33.2 GB large, very low quality loss - recommended
Nous-Hermes-2-Mixtral-8x7B-DPO-Q5_K_S.gguf Q5_K_S 5 32.2 GB large, low quality loss - recommended
Nous-Hermes-2-Mixtral-8x7B-DPO-Q6_K.gguf Q6_K 6 38.4 GB very large, extremely low quality loss
Nous-Hermes-2-Mixtral-8x7B-DPO-Q8_0.gguf Q8_0 8 49.6 GB very large, extremely low quality loss - not recommended
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GGUF
Model size
46.7B params
Architecture
llama

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

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