insuhan / hyper-attnLinks
☆81Updated last year
Alternatives and similar repositories for hyper-attn
Users that are interested in hyper-attn are comparing it to the libraries listed below
Sorting:
- The simplest implementation of recent Sparse Attention patterns for efficient LLM inference.☆70Updated last week
- Fast and memory-efficient exact attention☆68Updated 3 months ago
- A MAD laboratory to improve AI architecture designs 🧪☆120Updated 6 months ago
- Understand and test language model architectures on synthetic tasks.☆217Updated 2 weeks ago
- Tree Attention: Topology-aware Decoding for Long-Context Attention on GPU clusters☆126Updated 6 months ago
- ☆147Updated 2 years ago
- ☆109Updated last year
- Yet another random morning idea to be quickly tried and architecture shared if it works; to allow the transformer to pause for any amount…☆54Updated last year
- ☆76Updated 3 months ago
- nanoGPT-like codebase for LLM training☆98Updated last month
- Triton-based implementation of Sparse Mixture of Experts.☆219Updated 6 months ago
- Experiment of using Tangent to autodiff triton☆79Updated last year
- The source code of our work "Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models" [AISTATS …☆59Updated 8 months ago
- ☆53Updated last year
- Code for NeurIPS 2024 Spotlight: "Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations"☆74Updated 7 months ago
- ☆114Updated 3 weeks ago
- Code for exploring Based models from "Simple linear attention language models balance the recall-throughput tradeoff"☆235Updated 2 weeks ago
- The simplest, fastest repository for training/finetuning medium-sized GPTs.☆134Updated this week
- ☆53Updated 8 months ago
- Triton Implementation of HyperAttention Algorithm☆48Updated last year
- A library for unit scaling in PyTorch☆125Updated 6 months ago
- A fusion of a linear layer and a cross entropy loss, written for pytorch in triton.☆68Updated 10 months ago
- ☆45Updated last year
- The evaluation framework for training-free sparse attention in LLMs☆69Updated this week
- ☆105Updated last year
- Language models scale reliably with over-training and on downstream tasks☆97Updated last year
- Flash-Muon: An Efficient Implementation of Muon Optimizer☆131Updated last week
- Stick-breaking attention☆57Updated last week
- Implementation of Infini-Transformer in Pytorch☆111Updated 5 months ago
- ☆105Updated 9 months ago