File size: 344 Bytes
aaa284f
c4992d8
aaa284f
573bfdb
aaa284f
c4992d8
852da30
6bca4ae
c4992d8
1c1148e
aaa284f
1
2
3
4
5
6
7
8
9
10
11
import gradio as gr
from transformers import pipeline

pipe = pipeline(task="sentiment-analysis", model="amaldevc/nlp_sentiment")

def predict(review):
    pred = pipe.predict(review)
    return pred[0]["label"] + " with score " + str(pred[0]["score"])

iface = gr.Interface(fn=predict, inputs=gr.Textbox(), outputs=gr.Textbox())
iface.launch()