---
tags:
- gguf
- llama.cpp
- unsloth
- mind_call
- function_call
datasets:
- frshafi/mind_call
language:
- en
base_model:
- meta-llama/Llama-3.2-3B-Instruct
metrics:
- accuracy: 88%
---

# health_function_call_llama3.2_3b_gguf: GGUF

A fine-tuned **Llama 3.2 3B GGUF model** designed for **structured function calling in healthcare edge devices**.Trained to convert natural 
language health queries into **JSON-based function calls**.

Base Model: LLama 3.2 3B

Fine Tuning: Parameter Efficient Fine Tuning. Targeted all linear layers (Q, K, V, O, gate, up, down), the 
model learned complex mapping logic while maintaining a tiny 10.5 MB adapter footprint.

Quantization: Exported to GGUF (Q4_K_M) format.

Dataset: The model is trained on the MindCall Dataset, a curated synthetic collection of 5,000+ high-fidelity health interaction pairs.

## 🚀 Key Features

- Converts user queries → structured API calls
- Lightweight GGUF format (runs locally via llama.cpp)
- Optimized for deterministic outputs (low temperature)
- Supports reasoning via `<think>` tags

## 📦 Model Files

- `Llama-3.2-3B-Instruct.Q4_K_M.gguf`

## ⚡ Quick Start (Python)

### Install dependencies

```bash
pip install llama-cpp-python huggingface_hub

```

### Load the model
``` code
from llama_cpp import Llama

llm = Llama.from_pretrained(
    repo_id="ramgovindv/health_function_call_llama3.2_3b_gguf",
    filename="Llama-3.2-3B-Instruct.Q4_K_M.gguf",
)
```

### Inference
``` code
query = "I am feeling dizzy for 2 days"

prompt = f"""
You are an API generator.
Return JSON in this format:
{{
"name": "function_name",
"parameters": {{
    "key": "value"
}}
}}
User query:
{query}
JSON:
"""

response = llm.create_chat_completion(
    messages=[{"role": "user", "content": prompt}],
    temperature=0.1
)
output = response["choices"][0]["message"]["content"]
print(output)
```

## Output
```code
<think>
User has dizziness → likely need blood pressure check
</think>

<function>
{
  "name": "get_blood_pressure_data",
  "parameters": {
    "num_days": 2
  }
}
</function>
```
```<think>``` → reasoning <br>
```<function>``` → actual function call



[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)