srush / do-we-need-attentionLinks
☆166Updated last year
Alternatives and similar repositories for do-we-need-attention
Users that are interested in do-we-need-attention are comparing it to the libraries listed below
Sorting:
- Understand and test language model architectures on synthetic tasks.☆217Updated last week
- ☆78Updated 11 months ago
- some common Huggingface transformers in maximal update parametrization (µP)☆80Updated 3 years ago
- A MAD laboratory to improve AI architecture designs 🧪☆120Updated 6 months ago
- Language models scale reliably with over-training and on downstream tasks☆97Updated last year
- The simplest, fastest repository for training/finetuning medium-sized GPTs.☆134Updated this week
- Code to reproduce "Transformers Can Do Arithmetic with the Right Embeddings", McLeish et al (NeurIPS 2024)☆190Updated last year
- Code for exploring Based models from "Simple linear attention language models balance the recall-throughput tradeoff"☆235Updated 2 weeks ago
- ☆37Updated last year
- Minimal (400 LOC) implementation Maximum (multi-node, FSDP) GPT training☆127Updated last year
- Code for the paper "The Impact of Positional Encoding on Length Generalization in Transformers", NeurIPS 2023☆136Updated last year
- Experiment of using Tangent to autodiff triton☆79Updated last year
- ☆53Updated last year
- Inference code for LLaMA models in JAX☆118Updated last year
- nanoGPT-like codebase for LLM training☆98Updated last month
- Multipack distributed sampler for fast padding-free training of LLMs☆191Updated 10 months ago
- ☆303Updated last year
- ☆53Updated last year
- A puzzle to learn about prompting☆128Updated 2 years ago
- WIP☆93Updated 10 months ago
- A simple library for scaling up JAX programs☆139Updated 7 months ago
- Experiments around a simple idea for inducing multiple hierarchical predictive model within a GPT☆214Updated 10 months ago
- Some personal experiments around routing tokens to different autoregressive attention, akin to mixture-of-experts☆119Updated 8 months ago
- The simplest implementation of recent Sparse Attention patterns for efficient LLM inference.☆70Updated last week
- JAX Synergistic Memory Inspector☆174Updated 11 months ago
- A toolkit for scaling law research ⚖☆49Updated 4 months ago
- seqax = sequence modeling + JAX☆159Updated last week
- ☆147Updated 2 years ago
- Experiments for efforts to train a new and improved t5☆77Updated last year
- Explorations into the recently proposed Taylor Series Linear Attention☆99Updated 10 months ago