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Model: second-state/Llama-3-Groq-8B-Tool-Use-GGUF
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---
license: llama3
model_name: Llama-3-Groq-8B-Tool-Use
base_model: Groq/Llama-3-Groq-8B-Tool-Use
model_creator: Groq
inference: false
pipeline_tag: text-generation
quantized_by: Second State Inc.
language:
- en
---
<!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://github.com/LlamaEdge/LlamaEdge/raw/dev/assets/logo.svg" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
<!-- header end -->
# Llama-3-Groq-8B-Tool-Use-GGUF
## Original Model
[Groq/Llama-3-Groq-8B-Tool-Use](https://huggingface.co/Groq/Llama-3-Groq-8B-Tool-Use)
## Run with LlamaEdge
- LlamaEdge version: [v0.12.4](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.12.4)
- Prompt template
- Prompt type: `groq-llama3-tool`
- Prompt string
```text
<|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
```bash
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](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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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| |
*Quantized with llama.cpp b3405.*

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{
"_name_or_path": "meta-llama/Meta-Llama-3-8B-Instruct",
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": 128009,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 8192,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 8,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 500000.0,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.41.2",
"use_cache": false,
"vocab_size": 128262
}

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{"framework":"other","task":"text-generation"}