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import gradio as gr
from transformers import pipeline
"""pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-en-es")
def predict(text):
return pipe(text)[0]["translation_text"]
demo = gr.Interface(
fn=predict,
inputs='text',
outputs='text',
)"""
pipe = pipeline("sentiment-analysis", model="michellejieli/emotion_text_classifier")
def predict(text):
return pipe(text)[0]["label"], pipe(text)[0]['score']
demo = gr.Interface(
fn = predict,
inputs = gr.Textbox(placeholder="Text here ..."),
outputs = ['text', 'number']
)
demo.launch()
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