hima06varshini/TeluguTranslatica

English-to-Telugu Translation Model 🏆

📌 Model Overview

This is a Neural Machine Translation (NMT) model trained to translate English sentences into Telugu using Transformer-based architectures.

• ✅ Handles complex sentence structures
• ✅ Supports general & conversational language
• ✅ Fine-tuned on English-Telugu parallel corpora

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📖 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))