# lucidrains/memorizing-transformers-pytorch

<https://repo.masters-masters.com/en/repos/lucidrains/memorizing-transformers-pytorch>

[Home](https://repo.masters-masters.com/en) › [lucidrains](https://repo.masters-masters.com/en/owners/lucidrains) › [memorizing-transformers-pytorch](https://repo.masters-masters.com/en/repos/lucidrains/memorizing-transformers-pytorch)

lucidrains/memorizing-transformers-pytorch has 646 stars on GitHub. Its RepoMasters card: Alpha tier. Implementation of Memorizing Transformers (ICLR 2022)…

| Field | Value |
| --- | --- |
| Owner | [lucidrains](https://repo.masters-masters.com/en/owners/lucidrains) |
| Stars | 646 |
| Forks | 49 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2022 |
| Topics | artificial-intelligence, deep-learning, attention-mechanism, transformers, memory, retrieval, approximate-nearest-neighbors |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [lucidrains/memorizing-transformers-pytorch](https://github.com/lucidrains/memorizing-transformers-pytorch) |

## Repository

Implementation of Memorizing Transformers (ICLR 2022), attention net augmented with indexing and retrieval of memories using approximate nearest neighbors, in Pytorch

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.