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johko / computer-vision-course

This repo is the homebase of a community driven course on Computer Vision with Neural Networks. Feel free to join us on the Hugging Face discord: hf.co/join/discord
MIT License
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Selecting Frameworks and Implementing a MultiFramework Approach for the Course #26

Closed alperenunlu closed 9 months ago

alperenunlu commented 9 months ago

Framework Choice

To create a comprehensive course, we must select and commit to specific frameworks. I propose focusing on PyTorch and Jax due to their popularity and versatile applications.

MultiFramework Vs MonoFramework Approach

Consider using two or more frameworks for each lesson, providing both Jax and PyTorch code options. This enables learners to choose their preferred framework and facilitates Jax adoption for those already familiar with PyTorch.

Let's collect suggestions and insights on this matter.

adhiiisetiawan commented 9 months ago

Yess, I agree to focus on PyTorch and Jax

wonhyeongseo commented 9 months ago

+1. Also we can focus on PyTorch first, then expand to JAX and TensorFlow like in the transformers docs.

merveenoyan commented 9 months ago

JAX is not as popular as TensorFlow (you can check out pip install stats). https://pypistats.org/packages/jax https://pypistats.org/packages/tensorflow

I think it's best to ship PyTorch first given it's the most popular and most model classes and backbones are implemented for it. Also for transformers codebase, there are more models for TF than JAX.

johko commented 9 months ago

I also agree that we should focus on one framework (PyTorch) for now and make sure we get high quality content with that.