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# 🌐 MO — English to Odia Translator

MO is a Transformer-based sequence-to-sequence model fine-tuned for translating English text into Odia. It is designed to be lightweight, fast, and suitable for real-time applications such as web apps, voice assistants, and local language tools.

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## 🚀 Model Description

This model is based on the T5 (Text-to-Text Transfer Transformer) architecture and has been fine-tuned specifically for the English → Odia translation task. It takes English sentences as input and generates their corresponding Odia translations.

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## ✨ Features

* 🔤 High-quality English → Odia translation
* ⚡ Optimized for fast inference
* 🧠 Transformer-based (T5 architecture)
* 🌐 Suitable for web and API integration
* 🎤 Can be integrated with speech systems

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## 🧠 Intended Use

This model is intended for:

* Language translation applications
* Educational tools
* Regional language assistants
* Voice-enabled AI systems
* Web-based translation platforms

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## ⚙️ Usage

```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

model_name = "your-username/mo-odia-translator"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

text = "Translate this sentence strictly to Odia: Hello, how are you?"

inputs = tokenizer(text, return_tensors="pt")

outputs = model.generate(**inputs)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

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## 📊 Training Details

* Model: T5 (fine-tuned)
* Task: English → Odia Translation
* Framework: PyTorch
* Tokenizer: SentencePiece

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## ⚠️ Limitations

* May struggle with very long or complex sentences
* Performance depends on training data quality
* Limited domain generalization
* May produce less accurate results for idioms or slang

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## 🔮 Future Improvements

* Bidirectional translation (Odia ↔ English)
* Larger and more diverse dataset
* Improved handling of long sentences
* Quantized version for faster inference

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## 👨‍💻 Author

Developed by **Rohan Bose**

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## 📜 License

This model is released under the MIT License.

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## ⭐ Support

If you find this model useful, please consider giving it a ⭐ on Hugging Face.

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