---
license: apache-2.0
language:
- en
base_model:
- unsloth/Llama-3.2-11B-Vision-Instruct-bnb-4bit
---
# llama3-ayurveda-text-v4

🧠 **Model Name:** `llama3-ayurveda-text-v4`  
📚 **Base Model:** [`unsloth/Llama-3.2-11B-Vision-Instruct-bnb-4bit`](https://huggingface.co/unsloth/Llama-3.2-11B-Vision-Instruct-bnb-4bit)  
🧪 **Trained By:** AyurEze 
🏥 **Domain:** Ayurveda / Healthcare / Medical  
📍 **Language(s):** English, Tamil (bilingual capability for Ayurveda-related queries)  
🧵 **Quantization:** 4-bit (bnb)  
🧩 **Framework:** [Transformers](https://huggingface.co/docs/transformers), [PEFT](https://huggingface.co/docs/peft), [Unsloth](https://github.com/unslothai/unsloth)  

---

## 🧾 Model Description

This is a fine-tuned LoRA version of LLaMA 3.2 11B (bnb 4-bit) adapted for **Ayurvedic medicine** and **natural language generation in the healthcare domain**, with special emphasis on traditional Indian medical knowledge.

It is trained on a curated dataset of 110+ classical Ayurvedic drugs and herbs, slokas from **Bhavaprakasha**, **Bhaisajya Ratnavali**, and traditional usage explanations in both **English** and **Tamil**. The goal is to provide accurate, contextually grounded, and culturally sensitive answers to questions about Ayurveda.

---

## 💡 Use Cases

- 🧪 Integrate with RAG pipelines for Ayurveda apps like *AyurEze*  
- 🤖 Q&A assistant for traditional medicine consultations

---

## 🛠️ Training Details

- **Base Model:** `unsloth/Llama-3.2-11B-Vision-Instruct-bnb-4bit` (text-only use)
- **Adapter Type:** LoRA (using PEFT)
- **Library:** `unsloth`, `transformers`, `peft`
- **Quantization:** 4-bit bnb  
- **Epochs:** 1–3 depending on dataset size  
- **Batch Size:** 2 per device  
- **Data Format:** Instruction-tuned, chat-style prompts with messages key (`{"messages": [...]}`)

---

## 📊 Evaluation

| Metric        | Result      |
|---------------|-------------|
| Human Eval    | ✅ Relevant, accurate for domain-specific queries |
| Token Quality | ✅ Well-structured output for Ayurvedic prompts |
| Toxicity      | ✅ Low (clean dataset, domain-specific)          |

---

## 🔍 Sample Prompt

```json
{
  "messages": [
    { "role": "user", "content": "Explain the uses of Pippali in Ayurveda in simple Tamil." }
  ]
}