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Vector embeddings are generated using an ML approach that trains a model to turn data into numerical vectors. Typically, a deepconvolutional neural networkis used to train these types of models. The resulting embeddings are often dense -- all values are non-zero -- and high dimensional -- up...
dataset=lance.dataset("/tmp/test.lance")assertisinstance(dataset,pa.dataset.Dataset) Pandas df=dataset.to_table().to_pandas()df DuckDB importduckdb# If this segfaults, make sure you have duckdb v0.7+ installedduckdb.query("SELECT * FROM dataset LIMIT 10").to_df() ...
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