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🚀 Contributing to KerasHub 🚀 #1835
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@SamanehSaadat @divyashreepathihalli leaving you both assigned here so we can monitor this issue for comments and new contributors. I've pinned it to the top of our issue list (following Keras). |
hi there @mattdangerw @SamanehSaadat @divyashreepathihalli love to work on this ,if no one else is already working on it.need some guidelines to start . |
Hi @kernel-loophole! Thanks for your interest! Please checkout issues with contributions welcome tag. That's a good place to start. |
@SamanehSaadat really appreciated and i already check it .But most of the issues are assigned. |
Tagging @divyashreepathihalli here to help find issues that need contributors. |
@divyashreepathihalli is there any issue where i can contribute . |
Hi @kernel-loophole!!! Would you like to port VideoSwin transformer from KerasCV to KerasHub? - #1755 |
yes for sure |
Hey @mattdangerw, @SamanehSaadat, @divyashreepathihalli, I'm excited to dive into this project and start contributing! Could you point me toward any issues that could use attention? Additionally, I'd appreciate some guidance on ramping up and aligning with the project's workflows. Looking forward to collaborating! |
@SAIREDDY07 would you like to add CoCa to KerasHub? |
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KerasHub is a high-velocity open-source project. We welcome contributions!
Read our contributing guide for details on setting up an environment and testing code. Here's what you can help with:
Take up an issue related to the KerasHub launch
As part our KerasHub consolidation we will be moving models to this repo from KerasCV on an ongoing basis. We will tag good issues to pick up with the contributions welcome tag.
Check out TODOs
There are various TODOs in the codebase. You can do a quick search (e.g.
grep "TODO" keras_nlp/ -r
) and see if anything looks interesting to you. Make sure to ask in this thread before starting work on any item!Add a new pretrained model implementation
If you have a model you would like to see added, open an issue or comment here to make sure it's a good fit, and then we can work on porting the model to KerasHub and Keras 3.
Add new examples to keras.io
We can always use more high quality examples of using KerasHub pretrained models on keras.io. See the repo for instructions on contributing.
Add new notebooks to Kaggle
Adding a Kaggle notebook is a great way to share an interactive piece of work with the community. See Gemma notebooks to get an idea of what people are doing. You can do this with any Keras model available on Kaggle. Use a model in a notebook and make it public!
If you are not sure where to start, take a look at ongoing competitions and submit a notebook.
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