from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import gradio as gr
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)
        
# examples = [
#     ["how are you today?"],
#     ["Translate this sentence into another language."],
#     ["how to play a game"],
# ]

demo = gr.Interface(fn=language_translator, inputs='text',outputs='text',title='English To Tamil Translator')#examples=examples)
demo.launch(debug=True,share=True)