README.md

---
license: mit
datasets: Hemanth-thunder/en_ta
language:
- ta
- en
widget:
- text: Actor Vijay is competing an 2026 election.
- text: you need to study well for exams
---

## Model Details
- **Model Name**: English-Tamil-Translator
- **Model Type**: Deep Learning Model
- **Language**: Python
- **Task**: Language Translation

## How to Use
1. **Install Gemma Python Package**:
   ```bash
    pip install -q -U transformers==4.38.0
   ```

## Inference
1. **How to use the model in our notebook**:
```python
# Load model directly
import torch
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

checkpoint = "Mr-Vicky-01/English-Tamil-Translator"
tokenizer = AutoTokenizer.from_pretrained(checkpoint)
model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint)

def language_translator(text):
    tokenized = tokenizer([text], return_tensors='pt')
    out = model.generate(**tokenized, max_length=128)
    return tokenizer.decode(out[0],skip_special_tokens=True)

text_to_translate = "i have to play football now!"
output = language_translator(text_to_translate)
print(output)
```