yuzhenmao / IceFormerLinks
Implementation of IceFormer: Accelerated Inference with Long-Sequence Transformers on CPUs (ICLR 2024).
☆25Updated 3 weeks ago
Alternatives and similar repositories for IceFormer
Users that are interested in IceFormer are comparing it to the libraries listed below
Sorting:
- [ACL 2024] RelayAttention for Efficient Large Language Model Serving with Long System Prompts☆40Updated last year
- Accelerate LLM preference tuning via prefix sharing with a single line of code☆43Updated last month
- ☆32Updated last year
- Odysseus: Playground of LLM Sequence Parallelism☆75Updated last year
- Quantized Attention on GPU☆44Updated 8 months ago
- Linear Attention Sequence Parallelism (LASP)☆85Updated last year
- Repository for Sparse Finetuning of LLMs via modified version of the MosaicML llmfoundry☆42Updated last year
- ☆75Updated 2 months ago
- 32 times longer context window than vanilla Transformers and up to 4 times longer than memory efficient Transformers.☆48Updated 2 years ago
- ☆53Updated last year
- ACL 2023☆39Updated 2 years ago
- Open deep learning compiler stack for cpu, gpu and specialized accelerators☆19Updated last week
- [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…☆29Updated last year
- Repository for CPU Kernel Generation for LLM Inference☆26Updated 2 years ago
- Transformers components but in Triton☆34Updated 3 months ago
- ☆20Updated 3 months ago
- Benchmark tests supporting the TiledCUDA library.☆17Updated 8 months ago
- Summary of system papers/frameworks/codes/tools on training or serving large model☆57Updated last year
- TensorRT LLM Benchmark Configuration☆13Updated last year
- CUDA and Triton implementations of Flash Attention with SoftmaxN.☆72Updated last year
- Flash-Muon: An Efficient Implementation of Muon Optimizer☆152Updated last month
- ☆50Updated 2 months ago
- [ICML 2024] When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models☆33Updated last year
- Implementation for the paper: CMoE: Fast Carving of Mixture-of-Experts for Efficient LLM Inference☆23Updated 5 months ago
- Decoding Attention is specially optimized for MHA, MQA, GQA and MLA using CUDA core for the decoding stage of LLM inference.☆40Updated 2 months ago
- Framework to reduce autotune overhead to zero for well known deployments.☆79Updated 2 weeks ago
- [ICML24] Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for LLMs☆91Updated 8 months ago
- IntLLaMA: A fast and light quantization solution for LLaMA☆18Updated 2 years ago
- Beyond KV Caching: Shared Attention for Efficient LLMs☆19Updated last year
- Low-Rank Llama Custom Training☆23Updated last year