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# imports | |
from transformers import pipeline | |
import gradio as gr | |
# define nlp mask | |
model = "siebert/sentiment-roberta-large-english" | |
nlp = pipeline(model=model) # set device=0 to use GPU (CPU default, -1) | |
# Inference | |
def inference(sentence): | |
preds = nlp(sentence) | |
pred_sentiment = preds[0]["label"] | |
pred_score = preds[0]["score"] | |
return pred_sentiment, pred_score | |
# launch app | |
gr.Interface(inference, | |
inputs=[gr.inputs.Textbox(label="Sentiment to predict", default="I love this!")], | |
outputs=[gr.outputs.Textbox(type="auto", label="Predicted sentiment"), | |
gr.outputs.Textbox(type="auto", label="Predicted score")], | |
description="Sentiment analysis", | |
allow_flagging=False, | |
).launch(debug=True) |