---
license: apache-2.0
language:
- en
- ta
pipeline_tag: translation
tags:
- tamil
- text-to-text
---

## 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.**



## 🔥 Example Usage  

Load and test the model using **Hugging Face Transformers**:  

```python
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
# Load model and tokenizer
model_name = "aishu15/colloquial-tamil"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
# Function to translate text
def translate(text):
    inputs = tokenizer(text, return_tensors="pt")
    outputs = model.generate(**inputs, max_length=128)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)
# Example translations
test_sentences = [
    "This is so beautiful",
    "Bro, are you coming or not?",
    "My mom is gonna kill me if I don't reach home now!"
]
for sentence in test_sentences:
    print(f"English: {sentence}")
    print(f"Colloquial Tamil: {translate(sentence)}\n")