Hi folks,
I hope you are doing well. I wanted to tell y’all about the new ConvNeXt models [1] I have been converting for the past few days. Finally, they are available on TF-Hub [2]. The collection contains a total of 30 models that are categorised into two groups: classifier and feature extractor.
These models are NOT blackbox SavedModels i.e., they can be fully expanded into tf.keras.Model objects and one can call all the utility functions on them (example: .summary()). TF-Hub links to the models,
conversion code, off-the-shelf classification, and fine-tuning code are available in the GitHub repository [3]. There are some points in the repository that calls for contributions, so happy to welcome them if
anyone’s interested 
A huge shoutout to the ML-GDE team for providing GCP credits that made the validation of these models [4] possible. Also, thanks to @vasudevgupta, @lgusm, and Willi Gierke for helping out. Happy to address any feedback and answer any questions.
References:
[1] https://arxiv.org/abs/2201.03545
[2] TensorFlow Hub 1
[3] GitHub - sayakpaul/ConvNeXt-TF: Includes PyTorch -> Keras model porting code for ConvNeXt family of models with fine-tuning and inference notebooks. 2
[4] ConvNeXt-TF/i1k_eval at main · sayakpaul/ConvNeXt-TF · GitHub 1