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app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+
+model_name = "yazied49/disabilityy_model_final"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
+
+def classify(text):
+    result = pipe(text)[0]
+    return f"Category: {result['label']}\nConfidence: {round(result['score'] * 100, 2)}%"
+
+gr.Interface(fn=classify, inputs="text", outputs="text", title="Disability Classifier").launch()

requirments.txt

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+transformers
+torch
+gradio