| from transformers import T5ForConditionalGeneration, T5Tokenizer | |
| import gradio as grad | |
| text2text_tkn= T5Tokenizer.from_pretrained("t5-small") | |
| mdl = T5ForConditionalGeneration.from_pretrained("t5-small") | |
| def text2text_sentiment(text): | |
| inp = "sst2 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="Sentiment") | |
| grad.Interface(text2text_sentiment, inputs=para, outputs=out).launch() | |