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Nemotron-Mini-4B-Instruct-GGUF

Original Model

nvidia/Nemotron-Mini-4B-Instruct

Run with LlamaEdge

  • LlamaEdge version: coming soon
  • Prompt template

    • Prompt type: nemotron-chat

    • Prompt string

      <extra_id_0>System
      {system_message}
      <extra_id_1>User
      {user_message_1}<extra_id_1>Assistant
      {assistant_message_1}
      <extra_id_1>User
      {user_message_2}<extra_id_1>Assistant
      {assistant_message_2}
      <extra_id_1>User
      {user_message_3}
      <extra_id_1>Assistant\n
      
      • Tool use

        <extra_id_0>System
        {system_message}
        <tool> {tool_1} </tool>
        <tool> {tool_2} </tool>
        
        
        <extra_id_1>User
        {user_message_1}<extra_id_1>Assistant
        <toolcall> {tool_call_message} </toolcall>
        <extra_id_1>Tool
        {tool_result_message}
        <extra_id_1>Assistant\n
        
  • Context size: 4096

  • Run as LlamaEdge service

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Nemotron-Mini-4B-Instruct-Q5_K_M.gguf \
      llama-api-server.wasm \
      --prompt-template nemotron-chat \
      --ctx-size 4096 \
      --model-name Nemotron-Mini-4B-Instruct
    
    • Tool use

      wasmedge --dir .:. --nn-preload default:GGML:AUTO:Nemotron-Mini-4B-Instruct-Q5_K_M.gguf \
        llama-api-server.wasm \
        --prompt-template nemotron-tool \
        --ctx-size 4096 \
        --model-name Nemotron-Mini-4B-Instruct
      
  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Nemotron-Mini-4B-Instruct-Q5_K_M.gguf \
      llama-chat.wasm \
      --prompt-template nemotron-chat \
      --ctx-size 4096
    

Quantized GGUF Models

Name Quant method Bits Size Use case
Nemotron-Mini-4B-Instruct-Q2_K.gguf Q2_K 2 3.35 GB smallest, significant quality loss - not recommended for most purposes
Nemotron-Mini-4B-Instruct-Q3_K_L.gguf Q3_K_L 3 4.69 GB small, substantial quality loss
Nemotron-Mini-4B-Instruct-Q3_K_M.gguf Q3_K_M 3 4.32 GB very small, high quality loss
Nemotron-Mini-4B-Instruct-Q3_K_S.gguf Q3_K_S 3 3.90 GB very small, high quality loss
Nemotron-Mini-4B-Instruct-Q4_0.gguf Q4_0 4 5.04 GB legacy; small, very high quality loss - prefer using Q3_K_M
Nemotron-Mini-4B-Instruct-Q4_K_M.gguf Q4_K_M 4 5.33 GB medium, balanced quality - recommended
Nemotron-Mini-4B-Instruct-Q4_K_S.gguf Q4_K_S 4 5.07 GB small, greater quality loss
Nemotron-Mini-4B-Instruct-Q5_0.gguf Q5_0 5 6.11 GB legacy; medium, balanced quality - prefer using Q4_K_M
Nemotron-Mini-4B-Instruct-Q5_K_M.gguf Q5_K_M 5 6.26 GB large, very low quality loss - recommended
Nemotron-Mini-4B-Instruct-Q5_K_S.gguf Q5_K_S 5 6.11 GB large, low quality loss - recommended
Nemotron-Mini-4B-Instruct-Q6_K.gguf Q6_K 6 7.25 GB very large, extremely low quality loss
Nemotron-Mini-4B-Instruct-Q8_0.gguf Q8_0 8 9.38 GB very large, extremely low quality loss - not recommended
Nemotron-Mini-4B-Instruct-f16.gguf f16 16 17.7 GB

Quantized with llama.cpp b3751

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

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