File size: 659 Bytes
bd7036e
 
b6a86d3
bd7036e
3498231
b63ce0a
bd7036e
 
b6a86d3
 
b63ce0a
bd7036e
 
 
 
de3e019
 
 
bd7036e
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
import gradio as gr
from transformers import pipeline
import os

model = pipeline("text-classification", model="i0xs0/Emotion_Detection", tokenizer="i0xs0/Emotion_Detection")


    
def predict_emotion(text):


    results = model(text)  
    return {item["label"]: item["score"] for item in results}


#theme = gr.themes.Ocean()
theme = gr.themes.Glass()


demo = gr.Interface(
    fn=predict_emotion,                
    inputs=gr.Textbox(label="Input Text"),  
    outputs=gr.Label(label="Emotion"),
    title="Emotion Classifier",
    description="Enter a text to classify its emotion.",
    allow_flagging="never",  

    theme=theme  
)


demo.launch()