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feifeibear / long-context-attention

USP: Unified (a.k.a. Hybrid, 2D) Sequence Parallel Attention for Long Context Transformers Model Training and Inference

Why this job: works in the areas we cover, but does not say which job it does

What it does

This repo provides a sequence parallel approach that synergizes the strengths of two popular distributed attentions, i.e. DeepSpeed-Ulysses-Attention and Ring-Attention, delivering a more general and stronger versatility and better performance. The project is built on zhuzilin/ring-flash-attention and refers to the DeepSpeed-Ulysses.

Get started

No single install command. Read the steps in the README (opens in new tab)

Maintenance
Active
Last commit 55 days ago
Stars
696
On GitHub
Licence
Apache-2.0
Allows business use
Downloads for
None listed
No release files
Latest version
0.6.4
Released 10 months ago
Built with
Python
98% of the code

Is it looked after?

Contributors
3
Last 90 days
Issues
72% closed
11 still open
Pull requests
129 merged
4 waiting
Releases
18
1 in the last year
  • No contributing guide
  • No security policy
  • No code of conduct
More: languages, topics and project record

Languages

  • Python 98%
  • Shell 2%

Topics

  • attention-is-all-you-need
  • llm-inference
  • llm-training
  • pytorch
  • ring-attention
  • deepspeed-ulysses

Project record

  • JobOther AI tools
  • StatusListed
  • Commits265
  • Forks86
  • Watching5
  • Stars in 28 days0
  • CreatedMar 27, 2024
  • First seen by usNov 7, 2026
  • CheckedNov 10, 2026

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