Neodac-mini: Northeast India Cultural AI Model

Name: neodac
Rating: 2.5 (11 reviews)

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

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.