English-to-Telugu Translation Model π
π Model Overview
This is a Neural Machine Translation (NMT) model trained to translate English sentences into Telugu using Transformer-based architectures.
- β Handles complex sentence structures
- β Supports general & conversational language
- β Fine-tuned on English-Telugu parallel corpora
π How to Use the Model
You can load this model using Hugging Face Transformers:
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
model_name = "hima06varshini/english-to-telugu-translation"
token = "YOUR_ACCESS_TOKEN" # Replace with your Hugging Face token if required
# Load Model & Tokenizer
model = AutoModelForSeq2SeqLM.from_pretrained(model_name, token=token)
tokenizer = AutoTokenizer.from_pretrained(model_name, token=token)
def translate(text):
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
# Example Translation
text = "Hello, how are you?"
print(translate(text))
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