Llama-3.2-3B-Instruct-GGUF

Original Model

meta-llama/Llama-3.2-3B-Instruct

Run with LlamaEdge

  • LlamaEdge version: v0.14.5 and above

  • Prompt template

    • Prompt type for chat: llama-3-chat

      • Prompt string

        <|begin_of_text|><|start_header_id|>system<|end_header_id|>
        
        {{ system_prompt }}<|eot_id|><|start_header_id|>user<|end_header_id|>
        
        {{ user_message_1 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
        
        {{ model_answer_1 }}<|eot_id|><|start_header_id|>user<|end_header_id|>
        
        {{ user_message_2 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
        
    • Prompt type for tool use: llama-3-tool

      • Prompt string

        <|begin_of_text|><|start_header_id|>system<|end_header_id|>
        
        {system_message}<|eot_id|><|start_header_id|>user<|end_header_id|>
        
        Given the following functions, please respond with a JSON for a function call with its proper arguments that best answers the given prompt.
        
        Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}. Do not use variables.
        
        [{"type":"function","function":{"name":"get_current_weather","description":"Get the current weather in a given location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The city and state, e.g. San Francisco, CA"},"unit":{"type":"string","description":"The temperature unit to use. Infer this from the users location.","enum":["celsius","fahrenheit"]}},"required":["location","unit"]}}}]
        
        Question: {user_message}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
        
  • Context size: 128000

  • Run as LlamaEdge service

    • Chat

      wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3.2-3B-Instruct-Q5_K_M.gguf \
          llama-api-server.wasm \
          --prompt-template llama-3-chat \
          --ctx-size 128000 \
          --model-name Llama-3.2-3b
      
    • Tool use

      wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3.2-3B-Instruct-Q5_K_M.gguf \
          llama-api-server.wasm \
          --prompt-template llama-3-tool \
          --ctx-size 128000 \
          --model-name Llama-3.2-3b
      
  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3.2-3B-Instruct-Q5_K_M.gguf \
      llama-chat.wasm \
      --prompt-template llama-3-chat \
      --ctx-size 128000
    

Quantized GGUF Models

Name Quant method Bits Size Use case
Llama-3.2-3B-Instruct-Q2_K.gguf Q2_K 2 581 MB smallest, significant quality loss - not recommended for most purposes
Llama-3.2-3B-Instruct-Q3_K_L.gguf Q3_K_L 3 733 MB small, substantial quality loss
Llama-3.2-3B-Instruct-Q3_K_M.gguf Q3_K_M 3 691 MB very small, high quality loss
Llama-3.2-3B-Instruct-Q3_K_S.gguf Q3_K_S 3 642 MB very small, high quality loss
Llama-3.2-3B-Instruct-Q4_0.gguf Q4_0 4 771 MB legacy; small, very high quality loss - prefer using Q3_K_M
Llama-3.2-3B-Instruct-Q4_K_M.gguf Q4_K_M 4 808 MB medium, balanced quality - recommended
Llama-3.2-3B-Instruct-Q4_K_S.gguf Q4_K_S 4 776 MB small, greater quality loss
Llama-3.2-3B-Instruct-Q5_0.gguf Q5_0 5 893 MB legacy; medium, balanced quality - prefer using Q4_K_M
Llama-3.2-3B-Instruct-Q5_K_M.gguf Q5_K_M 5 912 MB large, very low quality loss - recommended
Llama-3.2-3B-Instruct-Q5_K_S.gguf Q5_K_S 5 893 MB large, low quality loss - recommended
Llama-3.2-3B-Instruct-Q6_K.gguf Q6_K 6 1.02 GB very large, extremely low quality loss
Llama-3.2-3B-Instruct-Q8_0.gguf Q8_0 8 1.32 GB very large, extremely low quality loss - not recommended
Llama-3.2-3B-Instruct-f16.gguf f16 16 2.48 GB

Quantized with llama.cpp b3807

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This model is not currently available via any of the supported third-party Inference Providers, and the model is not deployed on the HF Inference API.

Model tree for second-state/Llama-3.2-3B-Instruct-GGUF

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Collection including second-state/Llama-3.2-3B-Instruct-GGUF