metadata
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:
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")