🚀 English-to-Tamil Translation — Fine-Tuned M2M100 (Stage 3)
Model ID: gopi30/english-to-tamil-stage2
Model Type: M2M100ForConditionalGeneration
Language Pair: English ➡ Tamil
Framework: 🤗 Transformers
📌 Model Summary
This model is the Stage 3 fine-tuned version of Facebook's M2M100 (418M) Multilingual Machine Translation model for English-to-Tamil translation. It builds on the improvements made in Stage 2 and incorporates more targeted domain-specific training to enhance translation fluency, contextual accuracy, and Tamil grammar structure.
✅ Improvements Over Stage 2
- Trained with cleaner and more diverse parallel English-Tamil sentence pairs
- Better handling of idioms and complex sentence structures
- Enhanced translation consistency and Tamil morphology
- Optimized tokenizer usage for more accurate sentence segmentation
📈 Use Cases
- Translating English educational content to Tamil
- Localizing web and mobile apps for Tamil-speaking audiences
- Assisting in communication for native Tamil speakers
- Voice assistants and accessibility tools
🧩 Base Model
- Base:
facebook/m2m100_418M - Languages Fine-Tuned:
en➡ta
📦 Installation
Make sure you have the transformers library installed:
pip install transformers
Via Transformers Library
Code
from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
model_path = "gopi30/english-to-tamil-stage3"
model = M2M100ForConditionalGeneration.from_pretrained(model_path)
tokenizer = M2M100Tokenizer.from_pretrained(model_path)
def translate_en_to_ta(text):
tokenizer.src_lang = "en"
encoded = tokenizer(text, return_tensors="pt")
generated = model.generate(**encoded, forced_bos_token_id=tokenizer.get_lang_id("ta"))
return tokenizer.decode(generated[0], skip_special_tokens=True)
# Example
print(translate_en_to_ta("Hello!"))