ailab/distilbert-base-uncased-fin.../app.py

25 lines
858 B
Python

import gradio as gr
from transformers import pipeline, AutoTokenizer, AutoConfig, AutoModelForSequenceClassification
modelName="distilbert-base-uncased-finetuned-sst-2-english"
tokenizer = AutoTokenizer.from_pretrained(modelName)
model = AutoModelForSequenceClassification.from_pretrained(modelName)
sentimentPipeline = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
def sentiment_analysis(text):
results = sentimentPipeline(text)
return f"Sentiment: {results[0].get('label')}, Score: {results[0].get('score'):.2f}"
demo = gr.Interface(fn=sentiment_analysis,
inputs='text',
outputs='text',
title = "文本情感分析"
)
if __name__ == "__main__":
demo.queue(concurrency_count=3)
demo.launch(server_name = "0.0.0.0", server_port = 7028)