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admchiem
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d8e1c23
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Parent(s):
ca36db7
Amélioration du texte de description et du titre
Browse files- __pycache__/inference.cpython-39.pyc +0 -0
- app.py +17 -5
- inference.py +4 -3
__pycache__/inference.cpython-39.pyc
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Binary file (4.72 kB). View file
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app.py
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@@ -1,16 +1,28 @@
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import gradio as gr
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from inference import model
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def predict_intent(text):
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result = model.predict(text)
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return f"Intent: {result['intent']}\
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iface = gr.Interface(
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fn=predict_intent,
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inputs=gr.Textbox(lines=2, placeholder="Enter a sentence..."),
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outputs="text",
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title="Intent & OOS Detector",
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description="
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)
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iface.launch()
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import gradio as gr
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from inference import model
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def predict_intent(text):
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result = model.predict(text)
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return f"Intent: {result['intent']}\nConfidence: {result['confidence']}\nOOS Score: {result['oos_score']:.3f}"
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iface = gr.Interface(
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fn=predict_intent,
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inputs=gr.Textbox(lines=2, placeholder="Enter a sentence...", value="Do you know Roger?"),
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outputs="text",
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title="Intent Classifier & OOS Detector",
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description="""
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<span style="font-size: 18px;">Type a sentence and get its predicted intent or detect if it's out-of-scope.</span>
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Supported intents include (not exhaustive): `weather`, `translate`, `play_music`,...
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The output will include:
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- The predicted intent (or `"oos"` if out-of-scope),
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- The confidence score of the predicted intent (or `None` if out-of-scope),
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- The OOS score (higher = more likely to be out-of-scope).
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🇬🇧 This model was trained on English-only data.
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"""
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)
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iface.launch()
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inference.py
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@@ -146,6 +146,7 @@ model = IntentClassifierWithOOS(
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device="cpu"
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)
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device="cpu"
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)
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if __name__ == "__main__":
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# Test with a sample query
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result = model.predict("Can you play some jazz music?")
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print(result)
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