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import gradio as gr | |
from transformers import pipeline | |
class UI: | |
def __init__(self): | |
self.model = pipeline("sentiment-analysis", model="lyrisha/distilbert-base-finetuned-sentiment") | |
def predict(self, text): | |
predictions = self.model(text) | |
return {p["label"]: p["score"] for p in predictions} | |
def launch(self): | |
demo = gr.Interface( | |
fn=self.predict, | |
inputs="textbox", | |
outputs=gr.Label(num_top_classes=2), | |
title="Check the mood of the sentence", | |
description="The model was trained on 'imdb' and 'glue sst2' dataset to classify sentences as 'positive' or 'negative' attitude.", | |
examples=[["Great news! My reality check just bounced."], | |
["I'm not arguing, I'm just explaining why I'm right."], | |
["I love deadlines, especially the whooshing sound they make as they fly by."], | |
["Life is like a box of chocolates. It's full of nuts."]] | |
) | |
return demo.launch() | |
UI().launch() | |