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Llama-3-Groq-70B-Tool-Use-GGUF

Original Model

Groq/Llama-3-Groq-70B-Tool-Use

Run with LlamaEdge

  • LlamaEdge version: v0.12.5

  • Prompt template

    • Prompt type: groq-llama3-tool

    • Prompt string

      <|start_header_id|>system<|end_header_id|>
      
      You are a function calling AI model. You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows:
      <tool_call>
      {"name": <function-name>,"arguments": <args-dict>}
      </tool_call>
      
      Here are the available tools:
      <tools> {
        "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"
          ]
        }
      }
      {
        "name": "predict_weather",
        "description": "Predict the weather in 24 hours",
        "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"
          ]
        }
      } </tools><|eot_id|><|start_header_id|>user<|end_header_id|>
      
      What is the weather like in San Francisco in Celsius?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
      
  • Context size: 8192

  • Run as LlamaEdge service

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3-Groq-70B-Tool-Use-Q5_K_M.gguf \
      llama-api-server.wasm \
      --prompt-template groq-llama3-tool \
      --ctx-size 8192 \
      --model-name Llama-3-Groq-70B
    
  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3-Groq-70B-Tool-Use-Q5_K_M.gguf \
      llama-chat.wasm \
      --prompt-template groq-llama3-tool \
      --ctx-size 8192
    

Quantized GGUF Models

Name Quant method Bits Size Use case
Llama-3-Groq-70B-Tool-Use-Q2_K.gguf Q2_K 2 26.4 GB smallest, significant quality loss - not recommended for most purposes
Llama-3-Groq-70B-Tool-Use-Q3_K_L.gguf Q3_K_L 3 37.1 GB small, substantial quality loss
Llama-3-Groq-70B-Tool-Use-Q3_K_M.gguf Q3_K_M 3 34.3 GB very small, high quality loss
Llama-3-Groq-70B-Tool-Use-Q3_K_S.gguf Q3_K_S 3 30.9 GB very small, high quality loss
Llama-3-Groq-70B-Tool-Use-Q4_0.gguf Q4_0 4 40.0 GB legacy; small, very high quality loss - prefer using Q3_K_M
Llama-3-Groq-70B-Tool-Use-Q4_K_M.gguf Q4_K_M 4 42.5 GB medium, balanced quality - recommended
Llama-3-Groq-70B-Tool-Use-Q4_K_S.gguf Q4_K_S 4 40.3 GB small, greater quality loss
Llama-3-Groq-70B-Tool-Use-Q5_0.gguf Q5_0 5 48.7 GB legacy; medium, balanced quality - prefer using Q4_K_M
Llama-3-Groq-70B-Tool-Use-Q5_K_M.gguf Q5_K_M 5 49.9 GB large, very low quality loss - recommended
Llama-3-Groq-70B-Tool-Use-Q5_K_S.gguf Q5_K_S 5 48.7 GB large, low quality loss - recommended
Llama-3-Groq-70B-Tool-Use-Q6_K-00001-of-00002.gguf Q6_K 6 29.8 GB very large, extremely low quality loss
Llama-3-Groq-70B-Tool-Use-Q6_K-00002-of-00002.gguf Q6_K 6 28.0 GB very large, extremely low quality loss
Llama-3-Groq-70B-Tool-Use-Q8_0-00001-of-00003.gguf Q8_0 8 29.8 GB very large, extremely low quality loss - not recommended
Llama-3-Groq-70B-Tool-Use-Q8_0-00002-of-00003.gguf Q8_0 8 29.8 GB very large, extremely low quality loss - not recommended
Llama-3-Groq-70B-Tool-Use-Q8_0-00003-of-00003.gguf Q8_0 8 15.4 GB very large, extremely low quality loss - not recommended
Llama-3-Groq-70B-Tool-Use-f16-00001-of-00005.gguf f16 16 30.0 GB
Llama-3-Groq-70B-Tool-Use-f16-00002-of-00005.gguf f16 16 29.6 GB
Llama-3-Groq-70B-Tool-Use-f16-00003-of-00005.gguf f16 16 29.6 GB
Llama-3-Groq-70B-Tool-Use-f16-00004-of-00005.gguf f16 16 29.6 GB
Llama-3-Groq-70B-Tool-Use-f16-00005-of-00005.gguf f16 16 22.2 GB

Quantized with llama.cpp b3463.

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Inference API
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