num_documents
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num_documents has 13 facts recorded in Dontopedia across 6 references, with 2 live disagreements.
Mostly:rdf:type(4), has value(3), equals(1)
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definesVariableDefines Variable(2)
- Example Implementation
ex:example-implementation - Example Indexivf Flat
ex:example-indexivf-flat
containsVariableContains Variable(1)
- Code Block 4869
ex:code-block-4869
hasSizeHas Size(1)
- Document Embeddings
ex:document-embeddings
Other facts (10)
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References (6)
ctx:claims/beam/f4875baf-2de8-4f32-b31f-0e5fd916dd32ctx:claims/beam/a8f9767f-e515-4c18-876d-5a6237129dbe- full textbeam-chunktext/plain1 KB
doc:beam/a8f9767f-e515-4c18-876d-5a6237129dbeShow excerpt
query_embedding = np.random.rand(1, 512).astype('float32') # Search the index distances, indices = index.search(query_embedding, k=10) print(distances) print(indices) ``` ->-> 4,22 [Turn 4869] Assistant: Certainly! FAISS is a powerful li…
ctx:claims/beam/dec68f27-fa07-4dd3-9e72-4e86e758bea4- full textbeam-chunktext/plain1 KB
doc:beam/dec68f27-fa07-4dd3-9e72-4e86e758bea4Show excerpt
- We use the `search` method to find the 10 nearest neighbors to the query embedding. The method returns the distances and indices of the nearest neighbors. ### Benefits of FAISS - **Reduced Memory Usage**: FAISS can store large number…
ctx:claims/beam/f4aef03b-af1f-48d6-9f2c-e041983c87f7ctx:claims/beam/c12a5314-5117-4beb-a829-e08beb503951- full textbeam-chunktext/plain1 KB
doc:beam/c12a5314-5117-4beb-a829-e08beb503951Show excerpt
dense_scores = np.random.rand(num_queries, num_documents) # Test queries test_queries = np.random.rand(num_queries, num_documents) predictions = [] for i in range(num_queries): query = test_queries[i] sparse_scores_i = sparse_scor…
ctx:claims/beam/b9f71d2d-9dd8-41f5-a372-36155652965d- full textbeam-chunktext/plain1 KB
doc:beam/b9f71d2d-9dd8-41f5-a372-36155652965dShow excerpt
prediction = rank_documents(query, sparse_scores_i, dense_scores_i) if prediction is not None: predictions.append(prediction) # Evaluate precision true_labels = np.random.randint(0, 2, size=(num_queries, num_documents)) # …
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