[FIXED] What is the difference between TFHub and Model Garden?

Issue

TensorFlow Hub is a repository for pre-trained models. Model Garden also keeps SOTA models and provides facilities for downloading and leveraging its models like TfHub, and both of them are created by TensorFlow.

Why did Tensorflowmake two concepts for a model repository?

When should we use TfHub for retrieving a well-known model, and when should we use Model Garden to download a model? What is the difference between them?

Solution

TF Hub provides trained models in SavedModel, TFLite, or TF.js format. These artifacts can be used for inference and some can be used in code for fine-tuning. TF Hub does not provide modeling library code to train your own models from scratch.

Model Garden is a modeling library for training BERT, image classification models, and more. Model Garden provides code for training your own models from scratch as well as some checkpoints to start from.

Answered By - kempy