Starred repositories
The fundamental package for scientific computing with Python.
📰 Must-read papers on KV Cache Compression (constantly updating 🤗).
[ICLR 2025] PEARL: Parallel Speculative Decoding with Adaptive Draft Length
CUDA Templates and Python DSLs for High-Performance Linear Algebra
The collection of awesome papers on alignment of diffusion models.
📰 Must-read papers and blogs on Speculative Decoding ⚡️
Lean 4 programming language and theorem prover
Intel® Optimization for Chainer*, a Chainer module providing numpy like API and DNN acceleration using MKL-DNN.
A CPU+GPU Profiling library that provides access to timeline traces and hardware performance counters.
Intel® Instrumentation and Tracing Technology (ITT) and Just-In-Time (JIT) APIs
🛠A lite C++ AI toolkit: 100+ models with MNN, ORT and TRT, including Det, Seg, Stable-Diffusion, Face-Fusion, etc.🎉
[NeurIPS 2024] Code for the paper "Diffusion of Thoughts: Chain-of-Thought Reasoning in Diffusion Language Models"
Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)
PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own.
Continuous builder and binary build scripts for pytorch
[NeurIPS 2025] SpatialLM: Training Large Language Models for Structured Indoor Modeling
[ICLR 2025] TabDiff: a Mixed-type Diffusion Model for Tabular Data Generation
TorchBench is a collection of open source benchmarks used to evaluate PyTorch performance.
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
Open-source high-performance RISC-V processor
📚LeetCUDA: Modern CUDA Learn Notes with PyTorch for Beginners🐑, 200+ CUDA Kernels, Tensor Cores, HGEMM, FA-2 MMA.🎉
My learning notes/codes for ML SYS.
Official Code for Paper "Think While You Generate: Discrete Diffusion with Planned Denoising" [ICLR 2025]
a language for fast, portable data-parallel computation
Official Repository for "Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress?" (Daniel P. Jeong, Saurabh Garg, Zachary C. Lipton, Michael Oberst) (EMNLP 2024, Oral)
经济学人(含音频)、纽约客、卫报、连线、大西洋月刊等英语杂志免费下载,支持epub、mobi、pdf格式, 每周更新