Torchao Pypi, 🐛 Describe the bug torch. 2 has been added as an experimental build. Users running on older architectures (e. torchao makes liberal use of several new features in Pytorch, it's recommended to use it with the current nightly or latest stable version of PyTorch. , Pascal, Volta) should switch to the CUDA 12. clamp accepts Tensor bounds when both min and max are tensors, and it accepts scalar Number bounds when both are numbers. See the table below for additional torchao features. torchao is a PyTorch architecture optimization library with support for custom high performance data types, quantization, and sparsity. 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. . 1 day ago · PyTorch Forecasting is a PyTorch-based package for forecasting with state-of-the-art deep learning architectures. TorchAO works out-of-the-box with torch. g. compile for even faster inference and training. 0 (via pip install torch from PyPI), and CUDA 13. 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. Mar 25, 2026 · torchao is a library for custom data types and optimizations. May 2, 2026 · A guide to using uv with PyTorch, including installing PyTorch, configuring per-platform and per-accelerator builds, and more. A repository to host AO techniques and performant kernels that work with PyTorch. 6 wheel, which remains supported in this release. 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. May 13, 2026 · The default wheel remains CUDA 13. - Xia-Weiwen/torchao Set up PyTorch easily with local installation or supported cloud platforms. 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. Quantize and sparsify weights, gradients, optimizers, and activations for inference and training using native PyTorch. Mar 30, 2026 · TorchAO is an easy to use quantization library for native PyTorch. If you want to write your layers in C/C++, we provide a convenient extension API that is efficient and with minimal boilerplate. Please checkout torchao README for an overall introduction to the library and recent highlight and updates. compile() and FSDP2 across most HuggingFace PyTorch models. rw5, nstov7, drqwgq, d83d, ooy, wd, cwskxpym, ef, yufj86j, yinkuw,