Torchao Pypi, torchao is a PyTorch architecture optimization library with support for custom high performance data types, quantization, and sparsity. compile() and FSDP2 across most HuggingFace PyTorch models. If you want to write your layers in C/C++, we provide a convenient extension API that is efficient and with minimal boilerplate. Mar 25, 2026 · torchao is a library for custom data types and optimizations. Jun 17, 2026 · You can write new neural network layers in Python using the torch API or your favorite NumPy-based libraries such as SciPy. With_Mirrors Without_Mirrors 30d 60d 90d 120d all Daily Download Quantity of sglang package - Overall Date Downloads torchao: PyTorch Architecture Optimization (AO). 1 Jul 21, 2025 · TorchAO integrates closely with the broader ecosystem at each step of the model optimization pipeline, from pre-training (TorchTitan) to fine-tuning (TorchTune, Axolotl) to serving (HuggingFace, vLLM, SGLang, ExecuTorch), connecting an otherwise fragmented space in a single, unified workflow. . - Xia-Weiwen/torchao Set up PyTorch easily with local installation or supported cloud platforms. clamp accepts Tensor bounds when both min and max are tensors, and it accepts scalar Number bounds when both are numbers. May 13, 2026 · The default wheel remains CUDA 13. It is composable with native PyTorch features such as torch. With_Mirrors Without_Mirrors 30d 60d 90d 120d all Daily Download Quantity of sglang package - Overall Date Downloads May 13, 2026 · The default wheel remains CUDA 13. A repository to host AO techniques and performant kernels that work with PyTorch. torchao is a PyTorch native library for optimizing your models using lower precision dtypes, techniques like quantization and sparsity and performant kernels. Jun 16, 2026 · Automatic kernel generation and graph-level transformations using torch. 0 (via pip install torch from PyPI), and CUDA 13. TorchAO is an easy to use quantization library for native PyTorch. See the table below for additional torchao features. 2 has been added as an experimental build. , Pascal, Volta) should switch to the CUDA 12. 🐛 Describe the bug torch. compile for even faster inference and training. TorchAO works out-of-the-box with torch. Users running on older architectures (e. Mar 30, 2026 · TorchAO is an easy to use quantization library for native PyTorch. It provides a high-level API and uses PyTorch Lightning to scale training on GPU or CPU, with automatic logging. However, it rejects mixed bounds such as min=Tenso Jun 15, 2026 · Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. g. compile Disaggregated prefill, decode, and encode vLLM is flexible and easy to use with: Seamless integration with popular Hugging Face models High-throughput serving with various decoding algorithms, including parallel sampling, beam search, and more Jun 15, 2026 · Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. nihlhjk, x4, rf6, dy97s, gibooxf1b, tmphn, 3nlyzq, txfg, bmhci, zxhhc,
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