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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("Finetuned_model/") | |
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 = [ | |
["hello everyone"], | |
["hardwork never fails."], | |
["A room without books is like a body without a soul."], | |
["The Sun is approximately 4.6 billion years older than Earth."], | |
] | |
demo = gr.Interface(fn=language_translator, inputs='text',outputs='text',title='English to Tamil Translator',examples=examples) | |
demo.launch(debug=True,share=True) |