# wmn-231314/diffusion-data-constraint

<https://repo.masters-masters.com/en/repos/wmn-231314/diffusion-data-constraint>

[Home](https://repo.masters-masters.com/en) › [wmn-231314](https://repo.masters-masters.com/en/owners/wmn-231314) › [diffusion-data-constraint](https://repo.masters-masters.com/en/repos/wmn-231314/diffusion-data-constraint)

wmn-231314/diffusion-data-constraint has 128 stars on GitHub. Its RepoMasters card: Prototype tier. Official PyTorch implementation and models for paper…

| Field | Value |
| --- | --- |
| Owner | [wmn-231314](https://repo.masters-masters.com/en/owners/wmn-231314) |
| Stars | 128 |
| Forks | 6 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | None |
| Created | 2025 |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [wmn-231314/diffusion-data-constraint](https://github.com/wmn-231314/diffusion-data-constraint) |

## Repository

Official PyTorch implementation and models for paper "Diffusion Beats Autoregressive in Data-Constrained Settings". We find diffusion models are significantly more data-efficient than standard left to right autoregressive models, due to their ability to learn from different token orderings.

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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