Rust Tokenizers
Rust-tokenizer offers high-performance tokenizers for modern language models, including WordPiece, Byte-Pair Encoding (BPE) and Unigram (SentencePiece) models
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Pytorch Encoding | 1,974 | 1 | a year ago | 130 | August 08, 2020 | 143 | mit | Python | ||
| A CV toolkit for my papers. | ||||||||||
| Mlbox | 1,403 | a year ago | 21 | August 25, 2020 | 26 | other | Python | |||
| MLBox is a powerful Automated Machine Learning python library. | ||||||||||
| Deeppurpose | 826 | 6 months ago | 13 | October 26, 2021 | 12 | bsd-3-clause | Jupyter Notebook | |||
| A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics) | ||||||||||
| Vectorhub | 543 |  | 1 | a year ago | 45 | September 28, 2021 | 8 | apache-2.0 | Python | |
| Vector Hub - Library for easy discovery, and consumption of State-of-the-art models to turn data into vectors. (text2vec, image2vec, video2vec, graph2vec, bert, inception, etc) | ||||||||||
| Amazing Feature Engineering | 485 | 7 months ago | Jupyter Notebook | |||||||
| Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself. | ||||||||||
| Multidim Positional Encoding | 429 | 3 months ago | 14 | June 17, 2022 | 1 | mit | Python | |||
| An implementation of 1D, 2D, and 3D positional encoding in Pytorch and TensorFlow | ||||||||||
| Vectorai | 299 |  | 4 | 6 months ago | 9 | June 04, 2021 | 12 | apache-2.0 | Python | |
| Vector AI — A platform for building vector based applications. Encode, query and analyse data using vectors. | ||||||||||
| Rust Tokenizers | 232 | | 7 | 7 months ago | 34 | October 01, 2023 | 4 | apache-2.0 | Rust | |
| Rust-tokenizer offers high-performance tokenizers for modern language models, including WordPiece, Byte-Pair Encoding (BPE) and Unigram (SentencePiece) models | ||||||||||
| Practicaldl | 176 | 2 years ago | apache-2.0 | Jupyter Notebook | ||||||
| A Practical Guide to Deep Learning with TensorFlow 2.0 and Keras materials for Frontend Masters course | ||||||||||
| Sat2graph | 112 | a year ago | 11 | mit | OpenEdge ABL | |||||
| Sat2Graph: Road Graph Extraction through Graph-Tensor Encoding | ||||||||||
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