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from sentence_transformers import SentenceTransformer |
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import gradio as gr |
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model = SentenceTransformer("pritamdeka/BioBERT-mnli-snli-scinli-scitail-mednli-stsb") |
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def embed_text(text): |
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embedding = model.encode(text, convert_to_numpy=True, normalize_embeddings=True).tolist() |
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return embedding |
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iface = gr.Interface( |
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fn=embed_text, |
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inputs=gr.Textbox(lines=5, label="Enter clinical text"), |
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outputs="json", |
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title="High-Accuracy Clinical Embeddings", |
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description="BioBERT fine-tuned for semantic similarity (STSB, MedNLI)" |
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) |
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iface.launch() |
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