metadata
license: mit
datasets: Hemanth-thunder/en_ta
language:
- ta
- en
widget:
- text: Actor Vijay is competing an 2026 election.
- text: you have to study well for exams
- text: The Sun is approximately 4.6 billion years older than Earth.
pipeline_tag: text2text-generation
Model Details
- Model Name: English-Tamil-Translator
- Model Type: Deep Learning Model
- Language: Python
- Task: Language Translation
How to Use
- Install Gemma Python Package:
pip install -q -U transformers==4.38.0
Inference
- How to use the model in our notebook:
# 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)