README.md

---
license: apache-2.0
language:
- ta
- en
pipeline_tag: text2text-generation
datasets:
- aishu15/aryaumeshl
---

## Usage

To use this model, you can either directly use the Hugging Face `transformers` library or you can use the model via the Hugging Face inference API.


### Model Information

Training Details

- **This model has been fine-tuned for English to Tamil translation.**
- **Training Duration: Over 10 hours**
- **Loss Achieved: 0.6**
- **Model Architecture**
- **The model architecture is based on the Transformer architecture, specifically optimized for sequence-to-sequence tasks.**

### Installation
To use this model, you'll need to have the `transformers` library installed. You can install it via pip:
```bash
pip install transformers
```
### Via Transformers Library

You can use this model in your Python code like this:

## Inference
1. **How to use the model in our notebook**:
```python
# Load model directly
import torch
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
checkpoint = "aishu15/English-to-Tamil"
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 = "hardwork never fail"
output = language_translator(text_to_translate)
print(output)
```