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Browse files- README.md +10 -2
- app.py +23 -0
- requirements.txt +3 -0
README.md
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---
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title: Sentiment Analysis
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colorFrom: blue
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sdk: gradio
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sdk_version: 5.11.0
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app_file: app.py
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pinned: false
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license: mit
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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---
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title: Sentiment Analysis
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emoji: π
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colorFrom: blue
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colorTo: green
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sdk: gradio
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sdk_version: 5.11.0
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app_file: app.py
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pinned: false
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license: mit
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tags:
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- sentiment-analysis
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- NLP
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- machine-learning
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- gradio
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- transformers
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models:
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- distilbert-base-uncased-finetuned-sst-2-english
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import gradio as gr
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from transformers import pipeline
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# Load model
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sentiment_model = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
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# Define function for inference
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def analyze_sentiment(text):
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results = sentiment_model(text)
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return f"Sentiment: {results[0]['label']} (Confidence: {results[0]['score']:.2f})"
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# Create Gradio interface
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interface = gr.Interface(
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fn=analyze_sentiment,
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inputs=gr.Textbox(lines=2, placeholder="Enter text here..."),
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outputs="text",
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title="Sentiment Analysis App",
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description="Enter a sentence to analyze its sentiment using a fine-tuned DistilBERT model.",
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)
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# Launch the app
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if __name__ == "__main__":
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interface.launch()
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requirements.txt
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torch
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gradio
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transformers
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