pytorch / aoLinks
PyTorch native quantization and sparsity for training and inference
☆2,219Updated this week
Alternatives and similar repositories for ao
Users that are interested in ao are comparing it to the libraries listed below
Sorting:
- PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily wri…☆1,384Updated this week
- A pytorch quantization backend for optimum☆977Updated 3 weeks ago
- A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper, Ada and Bla…☆2,587Updated this week
- A PyTorch native platform for training generative AI models☆4,125Updated this week
- Tile primitives for speedy kernels☆2,541Updated this week
- A unified library of state-of-the-art model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. …☆1,078Updated 2 weeks ago
- Minimalistic large language model 3D-parallelism training☆2,068Updated 3 weeks ago
- Puzzles for learning Triton☆1,801Updated 8 months ago
- Transformers-compatible library for applying various compression algorithms to LLMs for optimized deployment with vLLM☆1,690Updated last week
- FlashInfer: Kernel Library for LLM Serving☆3,448Updated this week
- [MLSys 2024 Best Paper Award] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration☆3,181Updated 2 weeks ago
- Minimalistic 4D-parallelism distributed training framework for education purpose☆1,619Updated 3 weeks ago
- Mirage: Automatically Generating Fast GPU Kernels without Programming in Triton/CUDA☆1,629Updated this week
- Official implementation of Half-Quadratic Quantization (HQQ)☆852Updated last week
- A subset of PyTorch's neural network modules, written in Python using OpenAI's Triton.☆563Updated 2 weeks ago
- Pipeline Parallelism for PyTorch☆775Updated 11 months ago
- SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX R…☆2,461Updated last week
- Helpful tools and examples for working with flex-attention☆904Updated 2 weeks ago
- Domain-specific language designed to streamline the development of high-performance GPU/CPU/Accelerators kernels☆1,472Updated this week
- [ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models☆1,461Updated last year
- GPU programming related news and material links☆1,642Updated 6 months ago
- MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.☆2,042Updated last month
- A Python-level JIT compiler designed to make unmodified PyTorch programs faster.☆1,056Updated last year
- FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.☆868Updated 10 months ago
- Kernl lets you run PyTorch transformer models several times faster on GPU with a single line of code, and is designed to be easily hackab…☆1,578Updated last year
- Schedule-Free Optimization in PyTorch☆2,193Updated 2 months ago
- Flash Attention in ~100 lines of CUDA (forward pass only)☆887Updated 7 months ago
- Muon is an optimizer for hidden layers in neural networks☆1,390Updated 3 weeks ago
- AutoAWQ implements the AWQ algorithm for 4-bit quantization with a 2x speedup during inference. Documentation:☆2,221Updated 2 months ago
- 🚀 Efficient implementations of state-of-the-art linear attention models☆2,987Updated this week