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274f636 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | import gradio as gr
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
# Load model
model_path = "yazied49/disabilityy_model_final"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForSequenceClassification.from_pretrained(model_path)
# Prediction function
def predict(text):
inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
with torch.no_grad():
outputs = model(**inputs)
probs = torch.nn.functional.softmax(outputs.logits, dim=1)
pred_id = torch.argmax(probs, dim=1).item()
confidence = torch.max(probs).item()
label = model.config.id2label[str(pred_id)] # تأكد إن id2label keys = strings
return f"{label} ({round(confidence * 100, 2)}%)"
# Create Gradio interface
demo = gr.Interface(fn=predict, inputs="text", outputs="text", title="Disability Classifier")
# Launch app
demo.launch()
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