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from transformers import T5ForConditionalGeneration, T5Tokenizer | |
import gradio as gr | |
model_name = "t5-small" | |
text2text_tokenizer = T5Tokenizer.from_pretrained(model_name) | |
model = T5ForConditionalGeneration.from_pretrained(model_name) | |
def text2text_sentiment(text): | |
input = "Sentiment analysis for this sentence:" + text | |
encoded = text2text_tokenizer(input, return_tensors="pt") | |
tokens = model.generate(**encoded) | |
response = text2text_tokenizer.batch_decode(tokens) | |
return response | |
in_para = gr.Textbox(lines=1, label="English text", placeholder="Text in English") | |
out = gr.Textbox(lines=1, label="Sentiment") | |
gr.Interface(text2text_sentiment, inputs=in_para, outputs=out) |