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Learning PyTorch

Just one of the things I'm learning. https://github.com/hchiam/learning

"PyTorch in 100 seconds": https://www.youtube.com/watch?v=ORMx45xqWkA

https://pytorch.org

https://pytorch.org/get-started/locally --> this website automatically suggests how to install locally

https://github.com/pytorch/examples --> example PyTorch code for quick starts, e.g. Image classification (MNIST) using Convnets, Training Imagenet Classifiers with Popular Networks, DCGAN, VAE, RL, time sequence prediction, translation, and much more

e.g.:

conda install pytorch torchvision -c pytorch

or I think I prefer this:

pip3 install torch torchvision

or minimally just:

pip3 install torch

There's much more in the docs, but here's a sample of some interesting pages:

Demo

# creates model.pth:
python3 demo_run_save_model.py

# and now model.pth can be used by:
python3 demo_use_model.py

Running PyTorch from C# or .Net

Stable Diffusion Colab

https://colab.research.google.com/drive/1roZqqhsdpCXZr8kgV_Bx_ABVBPgea3lX

PyTorch Cheat Sheets

https://www.datacamp.com/cheat-sheet/deep-learning-with-py-torch

https://pytorch.org/tutorials/beginner/ptcheat.html

Suggestions on how to learn PyTorch

https://www.datacamp.com/blog/how-to-learn-pytorch

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