Update app.py
Browse filesfix embedding dimension, add button
app.py
CHANGED
@@ -13,10 +13,11 @@ model = model.merge_and_unload()
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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description = st.text_input("Product description")
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review = st.text_input("Review")
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if description and review:
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input_texts = [
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f'query: {review}',
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f'passage: {description}'
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@@ -26,10 +27,13 @@ if description and review:
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query_embedding, doc_embedding = model(**batch_dict, return_dict=True).pooler_output
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similarity = torch.nn.functional.cosine_similarity(
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query_embedding, doc_embedding)
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threshold = 0.
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if similarity > threshold:
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st.write('Relevant')
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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st.header("Irrelevant Review Detections :sunglasses:")
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description = st.text_input("Product description")
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review = st.text_input("Review")
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if st.button("Detect") and description and review:
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input_texts = [
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f'query: {review}',
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f'passage: {description}'
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query_embedding, doc_embedding = model(**batch_dict, return_dict=True).pooler_output
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query_embedding = query_embedding.unsqueeze(0)
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doc_embedding = doc_embedding.unsqueeze(0)
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similarity = torch.nn.functional.cosine_similarity(
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query_embedding, doc_embedding)
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threshold = 0.83
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if similarity > threshold:
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st.write('Relevant')
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