license, model_name, base_model, model_creator, inference, pipeline_tag, quantized_by, language

license	model_name	base_model	model_creator	inference	pipeline_tag	quantized_by	language
llama3	Llama-3-Groq-8B-Tool-Use	Groq/Llama-3-Groq-8B-Tool-Use	Groq	false	text-generation	Second State Inc.	en

---

Llama-3-Groq-8B-Tool-Use-GGUF

Original Model

Groq/Llama-3-Groq-8B-Tool-Use

Run with LlamaEdge

• LlamaEdge version: v0.12.4

• 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-8B-Tool-Use-Q5_K_M.gguf \
    llama-api-server.wasm \
    --prompt-template groq-llama3-tool \
    --ctx-size 8192 \
    --model-name Llama-3-Groq-8B
  

Quantized GGUF Models

Name	Quant method	Bits	Size	Use case
Llama-3-Groq-8B-Tool-Use-Q2_K.gguf	Q2_K	2	3.18 GB	smallest, significant quality loss - not recommended for most purposes
Llama-3-Groq-8B-Tool-Use-Q3_K_L.gguf	Q3_K_L	3	4.32 GB	small, substantial quality loss
Llama-3-Groq-8B-Tool-Use-Q3_K_M.gguf	Q3_K_M	3	4.02 GB	very small, high quality loss
Llama-3-Groq-8B-Tool-Use-Q3_K_S.gguf	Q3_K_S	3	3.66 GB	very small, high quality loss
Llama-3-Groq-8B-Tool-Use-Q4_0.gguf	Q4_0	4	4.66 GB	legacy; small, very high quality loss - prefer using Q3_K_M
Llama-3-Groq-8B-Tool-Use-Q4_K_M.gguf	Q4_K_M	4	4.92 GB	medium, balanced quality - recommended
Llama-3-Groq-8B-Tool-Use-Q4_K_S.gguf	Q4_K_S	4	4.69 GB	small, greater quality loss
Llama-3-Groq-8B-Tool-Use-Q5_0.gguf	Q5_0	5	5.60 GB	legacy; medium, balanced quality - prefer using Q4_K_M
Llama-3-Groq-8B-Tool-Use-Q5_K_M.gguf	Q5_K_M	5	5.73 GB	large, very low quality loss - recommended
Llama-3-Groq-8B-Tool-Use-Q5_K_S.gguf	Q5_K_S	5	5.60 GB	large, low quality loss - recommended
Llama-3-Groq-8B-Tool-Use-Q6_K.gguf	Q6_K	6	6.60 GB	very large, extremely low quality loss
Llama-3-Groq-8B-Tool-Use-Q8_0.gguf	Q8_0	8	8.54 GB	very large, extremely low quality loss - not recommended
Llama-3-Groq-8B-Tool-Use-f16.gguf	f16	16	16.1 GB

Quantized with llama.cpp b3405.