PyDigger - unearthing stuff about Python


NameVersionSummarydate
deepsparse 1.7.1 An inference runtime offering GPU-class performance on CPUs and APIs to integrate ML into your application 2024-03-19 17:49:49
nncf 2.9.0 Neural Networks Compression Framework 2024-03-06 11:39:35
sparsify-nightly 1.7.0.20240304 Easy-to-use UI for automatically sparsifying neural networks and creating sparsification recipes for better inference performance and a smaller footprint 2024-03-05 13:38:57
deepsparse-nightly 1.7.0.20240304 An inference runtime offering GPU-class performance on CPUs and APIs to integrate ML into your application 2024-03-05 13:38:47
sparseml-nightly 1.7.0.20240304 Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models 2024-03-05 13:37:16
nm-magic-wand 0.2.0 SparseLinear layers 2024-03-01 20:47:51
sparsify 1.6.1 Easy-to-use UI for automatically sparsifying neural networks and creating sparsification recipes for better inference performance and a smaller footprint 2023-12-20 14:28:37
sparseml 1.6.1 Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models 2023-12-20 14:24:12
sparsezoo 1.6.1 Neural network model repository for highly sparse and sparse-quantized models with matching sparsification recipes 2023-12-20 14:23:57
deepsparse-ent 1.6.0 An inference runtime offering GPU-class performance on CPUs and APIs to integrate ML into your application 2023-12-04 16:24:07
optimum-deepsparse 0.1.0.dev1 Optimum DeepSparse is an extension of the Hugging Face Transformers library that integrates the DeepSparse inference runtime. DeepSparse offers GPU-class performance on CPUs, making it possible to run Transformers and other deep learning models on commodity hardware with sparsity. Optimum DeepSparse provides a framework for developers to easily integrate DeepSparse into their applications, regardless of the hardware platform. 2023-10-26 02:02:45
deepstruct 0.10.0 2023-01-18 11:46:06
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