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app.py

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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)

requirements.txt

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+transformers
+gradio
+torch
+sentencepiece