README.md

---
license: apache-2.0
base_model: google/gemma-3-1b-it
tags:
- gemma
- northeast-india
- cultural
- fine-tuned
- assam
- manipur
- nagaland
- mizoram
- tripura
- meghalaya
- arunachal-pradesh
- sikkim
- neodac-mini
language:
- en
pipeline_tag: text-generation
library_name: transformers
widget:
- example_title: Bihu Festival
  text: |
    <start_of_turn>user
    What is Bihu festival?<end_of_turn>
    <start_of_turn>model
- example_title: Hornbill Festival
  text: |
    <start_of_turn>user
    Tell me about Hornbill Festival.<end_of_turn>
    <start_of_turn>model
- example_title: Assamese Cuisine
  text: |
    <start_of_turn>user
    What is traditional Assamese cuisine?<end_of_turn>
    <start_of_turn>model
---

# Neodac-mini: Northeast India Cultural AI Model

**Neodac-mini** (Northeast India Cultural) is a specialized language model fine-tuned on cultural knowledge of Northeast India's eight states. Built on Google's Gemma 3 1B Instruct, Neodac-mini provides authentic, detailed responses about the rich cultural heritage of the region.

## 🎯 Model Overview

- **Base Model**: [google/gemma-3-1b-it](https://huggingface.co/google/gemma-3-1b-it)
- **Specialization**: Northeast India Cultural Knowledge
- **Training Data**: 6,205 culturally authentic Q&A pairs
- **Coverage**: All 8 Northeast Indian states
- **Languages**: English (with cultural context)

## 🌟 Key Features

### Cultural Domains Covered
- **Festivals & Celebrations**: Bihu, Hornbill, Losar, Chapchar Kut, etc.
- **Traditional Arts**: Dance forms, music, crafts, weaving
- **Cuisine**: Regional foods, cooking methods, traditional recipes
- **Tribal Heritage**: Community practices, languages, customs
- **Geography**: Cultural significance of places and landmarks
- **Literature**: Folk tales, oral traditions, regional literature

### Model Capabilities
- ✅ Accurate cultural information without hallucinations
- ✅ Detailed responses about regional traditions
- ✅ Authentic representation of tribal communities
- ✅ Contextual understanding of cultural nuances
- ✅ Preservation of cultural knowledge through AI

## 🚀 Quick Start

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

# Load model and tokenizer
tokenizer = AutoTokenizer.from_pretrained("MWirelabs/neodac-mini")
model = AutoModelForCausalLM.from_pretrained(
    "MWirelabs/neodac-mini",
    torch_dtype=torch.bfloat16,
    device_map="auto"
)

# Example usage
def ask_neodac-mini(question):
    prompt = f"<start_of_turn>user\n{question}<end_of_turn>\n<start_of_turn>model\n"
    inputs = tokenizer(prompt, return_tensors="pt")

    with torch.no_grad():
        outputs = model.generate(
            **inputs,
            max_length=300,
            temperature=0.7,
            do_sample=True,
            pad_token_id=tokenizer.eos_token_id
        )

    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return response.split("<start_of_turn>model\n")[-1].strip()

# Ask about Northeast India culture
response = ask_neodac-mini("What is the significance of bamboo in Northeast India?")
print(response)
```

## 📊 Training Details

### Dataset
- **Size**: 6,205 cultural Q&A pairs
- **Sources**: Regional cultural databases, wiki content, expert curation
- **Quality**: Manually verified for cultural authenticity
- **Split**: 90% training, 10% validation

### Training Configuration
- **Hardware**: NVIDIA A40 40GB
- **Epochs**: 5 (enhanced from initial 3)
- **Learning Rate**: 2e-5 (optimized for detailed responses)
- **Batch Size**: 8 per device
- **Precision**: bfloat16
- **Max Sequence Length**: 512 tokens

### Improvements Over Base Model
| Aspect | Base Gemma 3 1B-IT | Neodac-mini |
|--------|-------------------|---------|
| Cultural Accuracy | ❌ Hallucinations | ✅ Factually correct |
| Response Detail | ⚠️ Generic/brief | ✅ Rich & comprehensive |
| Regional Context | ❌ Limited knowledge | ✅ Deep cultural understanding |
| Tribal Information | ❌ Inaccurate/missing | ✅ Authentic representation |

## 🎪 Example Comparisons

### Question: "What is Bihu festival?"

**Base Model Response:**
> Claims Bihu is about Lord Shiva (incorrect)

**Neodac-mini Response:**
> Bihu is the most important festival of Assam, celebrated by all Assamese people. There are three Bihus that mark different stages of the agricultural calendar: Rongali (or Bohag) Bihu in spring, Kati (or Kongali) Bihu in autumn, and Magh (or Bhogali) Bihu in winter.

## 🎯 Use Cases

### Cultural Education
- Educational institutions teaching Northeast India studies
- Cultural preservation initiatives
- Tourism and travel information

### Research & Documentation
- Academic research on regional culture
- Cultural anthropology studies
- Digital heritage preservation

### Community Applications
- Cultural chatbots for tourism
- Educational tools for diaspora communities
- Content creation for cultural media

## ⚠️ Limitations

- **Geographic Scope**: Specialized for Northeast India only
- **Language**: Responses in English (cultural terms may be in local languages)
- **Temporal Knowledge**: Training data has knowledge cutoff
- **Bias Inheritance**: May inherit biases from base model and training data

## 🔬 Evaluation & Performance

The model was evaluated on cultural accuracy, response completeness, and factual correctness. Significant improvements were observed over the base model in all cultural domains.

## 📜 Citation

If you use Neodac-mini in your research or applications, please cite:

```bibtex
@misc{neodac2025,
  title={Neodac-mini: A Specialized Language Model for Northeast India Cultural Knowledge},
  author={MWire Labs},
  year={2025},
  publisher={Hugging Face},
  url={https://huggingface.co/MWirelabs/neodac-mini},
  note={Fine-tuned from google/gemma-3-1b-it for cultural preservation and education}
}
```

## 🤝 Contributing

Interested in improving Neodac-mini? We welcome:
- Additional cultural data from Northeast India
- Feedback on cultural accuracy
- Suggestions for new cultural domains
- Community validation of responses

## 📄 License

This model is released under the Apache 2.0 license, same as the base Gemma model.

## 🙏 Acknowledgments

- Google for the Gemma 3 1B-IT base model
- Cultural experts and communities of Northeast India
- Contributors to the cultural dataset
- Hugging Face for the platform and tools

---

*Neodac-mini represents a step forward in culturally-aware AI, preserving and making accessible the rich heritage of Northeast India through technology.*