Torchao Pypi, torchao is a PyTorch native library for optimizing your models using lower precision dtypes, techniques like quantization and sparsity and performant kernels. With_Mirrors Without_Mirrors 30d 60d 90d 120d all Daily Download Quantity of sglang package - Overall Date Downloads torchao: PyTorch Architecture Optimization (AO). If you want to write your layers in C/C++, we provide a convenient extension API that is efficient and with minimal boilerplate. 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. TorchAO is an easy to use quantization library for native PyTorch. A repository to host AO techniques and performant kernels that work with PyTorch. Please checkout torchao README for an overall introduction to the library and recent highlight and updates. TorchAO works out-of-the-box with torch. May 13, 2026 · The default wheel remains CUDA 13. 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. Mar 30, 2026 · TorchAO is an easy to use quantization library for native PyTorch. 2 has been added as an experimental build. 1 day ago · PyTorch Forecasting is a PyTorch-based package for forecasting with state-of-the-art deep learning architectures. Users running on older architectures (e. Mar 25, 2026 · torchao is a library for custom data types and optimizations. , Pascal, Volta) should switch to the CUDA 12. Quantize and sparsify weights, gradients, optimizers, and activations for inference and training using native PyTorch. It is composable with native PyTorch features such as torch. 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. It provides a high-level API and uses PyTorch Lightning to scale training on GPU or CPU, with automatic logging. 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. . Jun 16, 2026 · Automatic kernel generation and graph-level transformations using torch. compile() and FSDP2 across most HuggingFace PyTorch models. Stable release from Pypi which will default to CUDA 12. torchao is a PyTorch architecture optimization library with support for custom high performance data types, quantization, and sparsity.
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