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from transformers import pipeline
import gradio as gr
model_checkpoint = "MuntasirHossain/RoBERTa-base-finetuned-emotion"
model = pipeline("text-classification", model=model_checkpoint)
def classify(text):
label = model(text)[0]["label"]
return label
description = "This AI model is trained to classify texts expressing human emotion into different categories."
title = "Xoxo's Texts Expressing Emotion"
examples = [["He is very happy Today",
"NOTE Free Palestien"]]
theme = {
"container": {
"background-color": "#007bff",
"color": "#fff",
"padding": "20px",
},
"textbox": {
"background-color": "#fff",
"border-radius": "5px",
"padding": "10px",
"margin-bottom": "10px",
},
"button": {
"background-color": "#007bff",
"color": "#fff",
"padding": "10px",
"border-radius": "5px",
"cursor": "pointer",
},
"label": {
"color": "#fff",
},
}
gr.Interface(fn=classify,
inputs="textbox",
outputs="text",
title=title,
theme=theme,
description=description,
examples=examples,
).launch()
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