Apple releases CoreNet, a library for training deep neural networks
News Source : Github.com
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- Its expansion facilitated the training of foundational models, including LLMs.If you find our work useful, please cite the following paper: CoreNet: A library for training deep neural networks
- You can switch to such a path with the cd $(pwd -P) command.This section provides quick access and a brief description for important CoreNet directories.Publication project directories generally contain the following contents:Each model class is decorated by a @MODEL_REGISTRY.register(name="
", type=" ") decorator.</li> - You can find information about contributing to CoreNet in our contributing document.Please remember to follow our Code of Conduct.For license details, see LICENSE.CoreNet evolved from CVNets, to encompass a broader range of applications beyond computer vision.
- To use a model class in CoreNet training or evaluation, assign moels.
.name = in the YAML configuration.This code is developed by Sachin, and is now maintained by Sachin, Maxwell Horton, Mohammad Sekhavat, and Yanzi Jin.We welcome PRs from the community!</li> - You should access the repository on disk as if the path were case sensitive, i.e.
</ul></div> </div> </div>CoreNet is a deep neural network toolkit that allows researchers and engineers to train standard and novel small and largescale models for variety of tasks, including foundation models (e.g., CLIP a [+2968 chars]Must read Articles
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