Document Embeddings Generation
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-07.)
Document Embeddings Generation has 3 facts recorded in Dontopedia across 1 reference.
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raw canonical shape-checked rule-derived certifiedInbound mentions (1)
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containsStatementContains Statement(1)
- Code Block 4869
ex:code-block-4869
Other facts (3)
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| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Data Generation | [1] |
| Uses Method | Numpy Random Rand | [1] |
| Applies Conversion | Astype Conversion | [1] |
Timeline
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References (1)
ctx: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…
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