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app.py

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+from transformers import T5ForConditionalGeneration, T5Tokenizer
+import gradio as grad
+
+text2text_tkn= T5Tokenizer.from_pretrained("t5-small")
+mdl = T5ForConditionalGeneration.from_pretrained("t5-small")
+
+
+
+def text2text_acceptable_sentence(text):
+     inp = "cola sentence: "+text
+     enc = text2text_tkn(inp, return_tensors="pt")
+     tokens = mdl.generate(**enc)
+     response=text2text_tkn.batch_decode(tokens)
+     return response
+
+para=grad.Textbox(lines=1, label="English Text", placeholder="Text in English")
+out=grad.Textbox(lines=1, label="Whether the sentence is acceptable or not")
+grad.Interface(text2text_acceptable_sentence, inputs=para, outputs=out).launch()

requirements.txt

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+gradio
+transformers
+torch
+transformers[sentencepiece]