File size: 648 Bytes
2bc3e0b
a976097
 
2bc3e0b
 
a976097
2bc3e0b
a976097
 
 
2bc3e0b
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
import gradio as gr
from transformers import pipeline

# Load pre-trained sentiment analysis model
sentiment_model = pipeline("sentiment-analysis")

# Define function to use the model
def analyze_sentiment(text):
    result = sentiment_model(text)[0]
    return f"Label: {result['label']} | Confidence: {result['score']:.2f}"

# Create Gradio interface
demo = gr.Interface(
    fn=analyze_sentiment,
    inputs=gr.Textbox(lines=3, placeholder="Type a sentence here..."),
    outputs="text",
    title="Simple Sentiment Analyzer",
    description="Find out if your text is Positive or Negative using a BERT model."
)

# Launch the app
demo.launch()