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import gradio as gr |
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from transformers import AutoTokenizer, AutoModelForMultipleChoice |
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import torch |
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tokenizer = AutoTokenizer.from_pretrained("LeduBaSK/wmhds") |
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model = AutoModelForMultipleChoice.from_pretrained("LeduBaSK/wmhds") |
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def predict(question, a, b, c, d): |
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inputs = tokenizer([question]*4, [a,b,c,d], return_tensors="pt", padding=True, truncation=True) |
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with torch.no_grad(): |
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outputs = model(**inputs) |
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pred = torch.argmax(outputs.logits).item() |
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return ["A", "B", "C", "D"][pred] |
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gr.Interface( |
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fn=predict, |
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inputs=[ |
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gr.Textbox(label="Question"), |
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gr.Textbox(label="Option A"), |
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gr.Textbox(label="Option B"), |
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gr.Textbox(label="Option C"), |
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gr.Textbox(label="Option D") |
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], |
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outputs="text", |
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title="Medical QA with WMHDS" |
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).launch() |
