graphcore-research / unit-scaling-demoLinks
Unit Scaling demo and experimentation code
☆16Updated last year
Alternatives and similar repositories for unit-scaling-demo
Users that are interested in unit-scaling-demo are comparing it to the libraries listed below
Sorting:
- Repository for CPU Kernel Generation for LLM Inference☆27Updated 2 years ago
- QuIP quantization☆61Updated last year
- Repository for Sparse Finetuning of LLMs via modified version of the MosaicML llmfoundry☆42Updated last year
- ☆20Updated 7 months ago
- This repository contains code for the MicroAdam paper.☆21Updated 11 months ago
- Make triton easier☆49Updated last year
- Linear Attention Sequence Parallelism (LASP)☆87Updated last year
- [ACL 2024] RelayAttention for Efficient Large Language Model Serving with Long System Prompts☆40Updated last year
- The evaluation framework for training-free sparse attention in LLMs☆106Updated last month
- ☆58Updated 2 years ago
- FlexAttention w/ FlashAttention3 Support☆27Updated last year
- Using FlexAttention to compute attention with different masking patterns☆47Updated last year
- The source code of our work "Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models" [AISTATS …☆60Updated last year
- ☆71Updated 8 months ago
- Vortex: A Flexible and Efficient Sparse Attention Framework☆41Updated last week
- ☆113Updated last year
- Flexible simulator for mixed precision and format simulation of LLMs and vision transformers.☆51Updated 2 years ago
- [ACL 2025] Squeezed Attention: Accelerating Long Prompt LLM Inference☆54Updated last year
- ☆112Updated 3 weeks ago
- Quantize transformers to any learned arbitrary 4-bit numeric format☆49Updated 5 months ago
- Low-Rank Llama Custom Training☆23Updated last year
- Intel Gaudi's Megatron DeepSpeed Large Language Models for training☆15Updated 11 months ago
- DPO, but faster 🚀☆46Updated last year
- Awesome Triton Resources☆38Updated 7 months ago
- 32 times longer context window than vanilla Transformers and up to 4 times longer than memory efficient Transformers.☆49Updated 2 years ago
- ☆56Updated 6 months ago
- Fast and memory-efficient exact attention☆74Updated 9 months ago
- Advanced Ultra-Low Bitrate Compression Techniques for the LLaMA Family of LLMs☆110Updated last year
- Accelerate LLM preference tuning via prefix sharing with a single line of code☆51Updated 5 months ago
- ☆62Updated last week