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import gradio as gr | |
from transformers import pipeline | |
raw_model_name = 'distilbert-base-uncased' | |
raw_model = pipeline('sentiment-analysis', model=raw_model_name) | |
fine_tuned_model_name = 'distilbert-base-uncased-finetuned-sst-2-english' | |
fine_tuned_model = pipeline('sentiment-analysis', model=fine_tuned_model_name) | |
def get_model_output(input_text, model_choice): | |
raw_result = raw_model(input_text) | |
fine_tuned_result = fine_tuned_model(input_text) | |
return format_model_output(raw_result[0]), format_model_output(fine_tuned_result[0]) | |
def format_model_output(output): | |
return f"I am {output['score']*100:.2f}% sure that the sentiment is {output['label']}" | |
iface = gr.Interface( | |
fn=get_model_output, | |
title="DistilBERT Sentiment Analysis", | |
inputs=[ | |
gr.Textbox(label="Input Text"), | |
], | |
outputs=[ | |
gr.Textbox(label="Base DistilBERT output (distilbert-base-uncased)"), | |
gr.Textbox(label="Fine-tuned DistilBERT output") | |
], | |
) | |
iface.launch() | |