NVIDIA / TransformerEngineLinks
A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper, Ada and Blackwell GPUs, to provide better performance with lower memory utilization in both training and inference.
☆2,707Updated this week
Alternatives and similar repositories for TransformerEngine
Users that are interested in TransformerEngine are comparing it to the libraries listed below
Sorting:
- FlashInfer: Kernel Library for LLM Serving☆3,679Updated this week
- A unified library of state-of-the-art model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. …☆1,200Updated this week
- PyTorch native quantization and sparsity for training and inference☆2,309Updated this week
- Transformer related optimization, including BERT, GPT☆6,285Updated last year
- [ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models☆1,487Updated last year
- PyTorch extensions for high performance and large scale training.☆3,367Updated 4 months ago
- Tile primitives for speedy kernels☆2,650Updated this week
- Ongoing research training transformer language models at scale, including: BERT & GPT-2☆2,154Updated 3 weeks ago
- Pipeline Parallelism for PyTorch☆778Updated last year
- [MLSys 2024 Best Paper Award] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration☆3,236Updated last month
- MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.☆2,051Updated 2 months ago
- SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX R…☆2,488Updated this week
- Domain-specific language designed to streamline the development of high-performance GPU/CPU/Accelerators kernels☆1,584Updated this week
- Tutel MoE: Optimized Mixture-of-Experts Library, Support GptOss/DeepSeek/Kimi-K2/Qwen3 FP8/NVFP4/MXFP4☆902Updated last week
- Puzzles for learning Triton☆1,972Updated 9 months ago
- Automatically Discovering Fast Parallelization Strategies for Distributed Deep Neural Network Training☆1,828Updated this week
- Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".☆2,177Updated last year
- A PyTorch native platform for training generative AI models☆4,339Updated this week
- Mirage Persistent Kernel: Compiling LLMs into a MegaKernel☆1,756Updated this week
- Distributed Compiler based on Triton for Parallel Systems☆1,074Updated last week
- The Triton TensorRT-LLM Backend☆887Updated this week
- A Python-level JIT compiler designed to make unmodified PyTorch programs faster.☆1,062Updated last year
- Flash Attention in ~100 lines of CUDA (forward pass only)☆915Updated 8 months ago
- A CPU+GPU Profiling library that provides access to timeline traces and hardware performance counters.☆856Updated last week
- 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…☆1,583Updated last year
- 🚀 Accelerate inference and training of 🤗 Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization…☆3,066Updated this week
- A fast communication-overlapping library for tensor/expert parallelism on GPUs.☆1,091Updated last week
- Microsoft Automatic Mixed Precision Library☆618Updated 11 months ago
- A PyTorch Native LLM Training Framework☆861Updated last month
- [ICML 2024] Break the Sequential Dependency of LLM Inference Using Lookahead Decoding☆1,276Updated 5 months ago