Linear-Next/Linear-Next-Datasets
Linear Next Benchmark Linear Next is a comprehensive benchmark designed to fairly compare various efficient transformer architectures. This project evaluates different approaches including linear attention, sparse attention, and other model structures under identical training conditions and datasets. Overview The benchmark aims to provide an unbiased comparison of efficient transformer variants by ensuring all models are trained with the same datasets… See the full description on the dataset page: https://huggingface.co/datasets/Linear-Next/Linear-Next-Datasets.
| Author / organization | Linear-Next |
|---|---|
| Downloads | 587 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 8 May 2025 |
| Last updated at source | 11 May 2025 |
Recent changes
- 16 Oct 2026 Description: Linear Next Benchmark Linear Next is a comprehensive benchmark designed to fairly compare various efficient transformer architectures. This project evaluates different approaches including linear attention, sparse attention, and other model → Linear Next Benchmark Linear Next is a comprehensive benchmark designed to fairly compare various efficient transformer architectures. This project evaluates different approaches including linear attention, sparse attention, and other model
Changes detected by Silytics between refreshes of the source.
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 16 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.