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Building Blocks Python Packages

Python packages with the GitHub topic building-blocks. Sorted by monthly downloads, with stars and forks.
rapidsai
libraft-cu12

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

220K 1K 252
rapidsai
pylibraft-cu12

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

218K 1K 252
rapidsai
raft-dask-cu12

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

47K 1K 252
rapidsai
libraft-cu13

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

25K 1K 252
rapidsai
pylibraft-cu13

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

25K 1K 252
rapidsai
raft-dask-cu13

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

2K 1K 252
rapidsai
pylibraft-cu11

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

676 1K 252
rapidsai
raft-dask-cu11

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

615 1K 252
rapidsai
libraft-cu11

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

414 1K 252
    • Original data from PyPI, GitHub, and OSV; downloads served through ClickHouse
    • Sources & methodology