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Model: second-state/Llama-3-Groq-8B-Tool-Use-GGUF Source: Original Platform
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README.md
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README.md
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---
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license: llama3
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model_name: Llama-3-Groq-8B-Tool-Use
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base_model: Groq/Llama-3-Groq-8B-Tool-Use
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model_creator: Groq
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inference: false
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pipeline_tag: text-generation
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quantized_by: Second State Inc.
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language:
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- en
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---
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<!-- header start -->
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<!-- 200823 -->
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<div style="width: auto; margin-left: auto; margin-right: auto">
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<img src="https://github.com/LlamaEdge/LlamaEdge/raw/dev/assets/logo.svg" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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</div>
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<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
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<!-- header end -->
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# Llama-3-Groq-8B-Tool-Use-GGUF
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## Original Model
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[Groq/Llama-3-Groq-8B-Tool-Use](https://huggingface.co/Groq/Llama-3-Groq-8B-Tool-Use)
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## Run with LlamaEdge
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- LlamaEdge version: [v0.12.4](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.12.4)
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- Prompt template
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- Prompt type: `groq-llama3-tool`
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- Prompt string
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```text
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<|start_header_id|>system<|end_header_id|>
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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:
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<tool_call>
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{"name": <function-name>,"arguments": <args-dict>}
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</tool_call>
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Here are the available tools:
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<tools> {
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"name": "get_current_weather",
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"description": "Get the current weather in a given location",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "The city and state, e.g. San Francisco, CA"
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},
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"unit": {
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"type": "string",
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"description": "The temperature unit to use. Infer this from the users location.",
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"enum": [
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"celsius",
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"fahrenheit"
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]
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}
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},
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"required": [
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"location",
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"unit"
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]
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}
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}
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{
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"name": "predict_weather",
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"description": "Predict the weather in 24 hours",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "The city and state, e.g. San Francisco, CA"
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},
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"unit": {
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"type": "string",
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"description": "The temperature unit to use. Infer this from the users location.",
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"enum": [
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"celsius",
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"fahrenheit"
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]
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}
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},
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"required": [
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"location",
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"unit"
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]
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}
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} </tools><|eot_id|><|start_header_id|>user<|end_header_id|>
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What is the weather like in San Francisco in Celsius?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
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```
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- Context size: `8192`
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- Run as LlamaEdge service
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```bash
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wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3-Groq-8B-Tool-Use-Q5_K_M.gguf \
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llama-api-server.wasm \
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--prompt-template groq-llama3-tool \
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--ctx-size 8192 \
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--model-name Llama-3-Groq-8B
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```
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## Quantized GGUF Models
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| Name | Quant method | Bits | Size | Use case |
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| ---- | ---- | ---- | ---- | ----- |
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| [Llama-3-Groq-8B-Tool-Use-Q2_K.gguf](https://huggingface.co/second-state/Llama-3-Groq-8B-Tool-Use-GGUF/blob/main/Llama-3-Groq-8B-Tool-Use-Q2_K.gguf) | Q2_K | 2 | 3.18 GB| smallest, significant quality loss - not recommended for most purposes |
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| [Llama-3-Groq-8B-Tool-Use-Q3_K_L.gguf](https://huggingface.co/second-state/Llama-3-Groq-8B-Tool-Use-GGUF/blob/main/Llama-3-Groq-8B-Tool-Use-Q3_K_L.gguf) | Q3_K_L | 3 | 4.32 GB| small, substantial quality loss |
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| [Llama-3-Groq-8B-Tool-Use-Q3_K_M.gguf](https://huggingface.co/second-state/Llama-3-Groq-8B-Tool-Use-GGUF/blob/main/Llama-3-Groq-8B-Tool-Use-Q3_K_M.gguf) | Q3_K_M | 3 | 4.02 GB| very small, high quality loss |
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| [Llama-3-Groq-8B-Tool-Use-Q3_K_S.gguf](https://huggingface.co/second-state/Llama-3-Groq-8B-Tool-Use-GGUF/blob/main/Llama-3-Groq-8B-Tool-Use-Q3_K_S.gguf) | Q3_K_S | 3 | 3.66 GB| very small, high quality loss |
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| [Llama-3-Groq-8B-Tool-Use-Q4_0.gguf](https://huggingface.co/second-state/Llama-3-Groq-8B-Tool-Use-GGUF/blob/main/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 |
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| [Llama-3-Groq-8B-Tool-Use-Q4_K_M.gguf](https://huggingface.co/second-state/Llama-3-Groq-8B-Tool-Use-GGUF/blob/main/Llama-3-Groq-8B-Tool-Use-Q4_K_M.gguf) | Q4_K_M | 4 | 4.92 GB| medium, balanced quality - recommended |
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| [Llama-3-Groq-8B-Tool-Use-Q4_K_S.gguf](https://huggingface.co/second-state/Llama-3-Groq-8B-Tool-Use-GGUF/blob/main/Llama-3-Groq-8B-Tool-Use-Q4_K_S.gguf) | Q4_K_S | 4 | 4.69 GB| small, greater quality loss |
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| [Llama-3-Groq-8B-Tool-Use-Q5_0.gguf](https://huggingface.co/second-state/Llama-3-Groq-8B-Tool-Use-GGUF/blob/main/Llama-3-Groq-8B-Tool-Use-Q5_0.gguf) | Q5_0 | 5 | 5.60 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
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| [Llama-3-Groq-8B-Tool-Use-Q5_K_M.gguf](https://huggingface.co/second-state/Llama-3-Groq-8B-Tool-Use-GGUF/blob/main/Llama-3-Groq-8B-Tool-Use-Q5_K_M.gguf) | Q5_K_M | 5 | 5.73 GB| large, very low quality loss - recommended |
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| [Llama-3-Groq-8B-Tool-Use-Q5_K_S.gguf](https://huggingface.co/second-state/Llama-3-Groq-8B-Tool-Use-GGUF/blob/main/Llama-3-Groq-8B-Tool-Use-Q5_K_S.gguf) | Q5_K_S | 5 | 5.60 GB| large, low quality loss - recommended |
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| [Llama-3-Groq-8B-Tool-Use-Q6_K.gguf](https://huggingface.co/second-state/Llama-3-Groq-8B-Tool-Use-GGUF/blob/main/Llama-3-Groq-8B-Tool-Use-Q6_K.gguf) | Q6_K | 6 | 6.60 GB| very large, extremely low quality loss |
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| [Llama-3-Groq-8B-Tool-Use-Q8_0.gguf](https://huggingface.co/second-state/Llama-3-Groq-8B-Tool-Use-GGUF/blob/main/Llama-3-Groq-8B-Tool-Use-Q8_0.gguf) | Q8_0 | 8 | 8.54 GB| very large, extremely low quality loss - not recommended |
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| [Llama-3-Groq-8B-Tool-Use-f16.gguf](https://huggingface.co/second-state/Llama-3-Groq-8B-Tool-Use-GGUF/blob/main/Llama-3-Groq-8B-Tool-Use-f16.gguf) | f16 | 16 | 16.1 GB| |
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*Quantized with llama.cpp b3405.*
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