| import gradio as gr | |
| import pickle | |
| from transformers import pipeline | |
| def load_model(selected_model): | |
| with open(selected_model, 'rb') as file: | |
| loaded_model = pickle.load(file) | |
| return loaded_model | |
| encoder = { | |
| 'negative':'assets/negative.jpeg', | |
| 'neutral':'assets/neutral.jpeg', | |
| 'positive':'assets/positive.jpeg' | |
| } | |
| classifier = pipeline(task="zero-shot-classification", model="facebook/bart-large-mnli") | |
| def analyze_sentiment(text): | |
| results = classifier(text,["positive","negative",'neutral'],multi_label=True) | |
| mx = max(results['scores']) | |
| ind = results['scores'].index(mx) | |
| result = results['labels'][ind] | |
| return encoder[result] | |
| demo = gr.Interface(fn=analyze_sentiment, inputs="text", outputs="image", title="Sentiment Analysis") | |
| demo.launch(share=True) |