neuralmagic / compressed-tensorsLinks
A safetensors extension to efficiently store sparse quantized tensors on disk
☆135Updated 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☆327Updated this week
- Boosting 4-bit inference kernels with 2:4 Sparsity☆80Updated 10 months ago
- ☆195Updated 2 months ago
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆254Updated 8 months ago
- [ICLR'25] Fast Inference of MoE Models with CPU-GPU Orchestration☆215Updated 7 months ago
- Applied AI experiments and examples for PyTorch☆281Updated last month
- KV cache compression for high-throughput LLM inference☆132Updated 5 months ago
- A high-throughput and memory-efficient inference and serving engine for LLMs☆264Updated 9 months ago
- [NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization☆360Updated 11 months ago
- Fast Hadamard transform in CUDA, with a PyTorch interface☆201Updated last year
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆313Updated last year
- QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference☆116Updated last year
- Efficient LLM Inference over Long Sequences☆382Updated 2 weeks ago
- QQQ is an innovative and hardware-optimized W4A8 quantization solution for LLMs.☆133Updated 3 months ago
- Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.☆176Updated last week
- ☆139Updated 3 weeks ago
- This repository contains the experimental PyTorch native float8 training UX☆224Updated 11 months ago
- Load compute kernels from the Hub☆203Updated this week
- GEAR: An Efficient KV Cache Compression Recipefor Near-Lossless Generative Inference of LLM☆165Updated last year
- Code for data-aware compression of DeepSeek models☆36Updated last month
- 🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.☆205Updated this week
- ☆73Updated 3 months ago
- Fast Matrix Multiplications for Lookup Table-Quantized LLMs☆372Updated 3 months ago
- A Quirky Assortment of CuTe Kernels☆126Updated last week
- Collection of kernels written in Triton language☆136Updated 3 months ago
- PyTorch bindings for CUTLASS grouped GEMM.☆100Updated last month
- A general 2-8 bits quantization toolbox with GPTQ/AWQ/HQQ/VPTQ, and export to onnx/onnx-runtime easily.☆173Updated 3 months ago
- ☆106Updated 10 months ago
- Easy and Efficient Quantization for Transformers☆198Updated 2 weeks ago
- [ICLR2025] Breaking Throughput-Latency Trade-off for Long Sequences with Speculative Decoding☆121Updated 7 months ago