vllm-project / compressed-tensorsLinks
A safetensors extension to efficiently store sparse quantized tensors on disk
☆237Updated this week
Alternatives and similar repositories for compressed-tensors
Users that are interested in compressed-tensors are comparing it to the libraries listed below
Sorting:
- Fast low-bit matmul kernels in Triton☆424Updated this week
- ☆206Updated 8 months ago
- 🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.☆218Updated last week
- A high-throughput and memory-efficient inference and serving engine for LLMs☆267Updated last month
- Applied AI experiments and examples for PyTorch☆314Updated 5 months ago
- Efficient LLM Inference over Long Sequences☆394Updated 7 months ago
- Boosting 4-bit inference kernels with 2:4 Sparsity☆93Updated last year
- A unified library for building, evaluating, and storing speculative decoding algorithms for LLM inference in vLLM☆205Updated last week
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆276Updated 6 months ago
- This repository contains the experimental PyTorch native float8 training UX☆227Updated last year
- KV cache compression for high-throughput LLM inference☆150Updated 11 months ago
- [NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization☆401Updated last year
- Accelerating MoE with IO and Tile-aware Optimizations☆563Updated last week
- [ICLR'25] Fast Inference of MoE Models with CPU-GPU Orchestration☆258Updated last year
- PyTorch bindings for CUTLASS grouped GEMM.☆141Updated 8 months ago
- Triton-based implementation of Sparse Mixture of Experts.☆262Updated 3 months ago
- QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference☆119Updated last year
- ☆163Updated 7 months ago
- QQQ is an innovative and hardware-optimized W4A8 quantization solution for LLMs.☆154Updated 5 months ago
- QuTLASS: CUTLASS-Powered Quantized BLAS for Deep Learning☆163Updated 2 months ago
- ☆277Updated this week
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆335Updated last year
- Collection of kernels written in Triton language☆175Updated 9 months ago
- Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.☆319Updated this week
- Fast Hadamard transform in CUDA, with a PyTorch interface☆275Updated 3 months ago
- Load compute kernels from the Hub☆381Updated this week
- Cataloging released Triton kernels.☆289Updated 4 months ago
- ArcticInference: vLLM plugin for high-throughput, low-latency inference☆379Updated last week
- 🚀 Efficiently (pre)training foundation models with native PyTorch features, including FSDP for training and SDPA implementation of Flash…☆280Updated 2 months ago
- ring-attention experiments☆163Updated last year