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import gradio as gr | |
from transformers import pipeline | |
nlp = pipeline("text-classification") | |
def classify_text(input_text): | |
result = nlp(input_text)[0] | |
return result["label"], result["score"] | |
with gr.Blocks() as demo: | |
with gr.Row(): | |
with gr.Column(): | |
text_input = gr.Textbox(label="Enter text to classify") | |
classify_btn = gr.Button(value="Classify") | |
with gr.Column(): | |
label_output = gr.Textbox(label="Predicted label") | |
score_output = gr.Textbox(label="Score") | |
classify_btn.click(classify_text, inputs=text_input, outputs=[label_output, score_output], api_name="classify-text") | |
examples = gr.Examples(examples=["This is a positive review.", "This is a negative review."], | |
inputs=[text_input]) | |
demo.launch() |