eeshsaxena/rope-attention-research
PyTorch implementation of RoFormer's Rotary Position Embeddings (RoPE) with comprehensive tests, benchmarks, and documentation. Used in LLaMA, PaLM, GPT-NeoX.
ORIGINAL REPOSITORY
eeshsaxena/rope-attention-research ↗GitHub activity
- Stars
- 16
- Forks
- 0
- Open issues and PRs
- 6
- Repository size
- ~69 KB
- Default branch
- master
- Created
- Jul 15, 2026
- Repository updated
- Sep 7, 2026
- Last push
- Jul 15, 2026
- Language
- Python
- License
- MIT
Topics attention-mechanism · deep-learning · llama · machine-learning · nlp · position-encoding · pytorch · research-paper · rope · transformer
Repository-wide figures from GitHub, checked Nov 6, 2026. Stars are endorsements, not a Mega AI Hub quality rating. Repository size is GitHub’s estimate; a ZIP download may differ.
Resource information
- Original repository
- eeshsaxena/rope-attention-research
- Credit basis
- GitHub repository owner or organization; individual authorship is not asserted
- Publisher
- eeshsaxena
- Upstream last modified
- Sep 7, 2026
- Official website
- https://github.com/eeshsaxena/rope-attention-research
- Languages
- Python
- Access
- Open original GitHub repository; publisher terms apply
- Last checked
- Nov 6, 2026
- License
- MIT
- Last record update
- Nov 6, 2026