Instructions to use zeromodels/tf_efficientnet_b4_aa_in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use zeromodels/tf_efficientnet_b4_aa_in1k with KerasFormers:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Keras
How to use zeromodels/tf_efficientnet_b4_aa_in1k with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://zeromodels/tf_efficientnet_b4_aa_in1k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74f2c8230361c0d4e02d82a78f6914f696caf9e34e1e9eb7e33d320ad9a7d08c
- Size of remote file:
- 79.1 MB
- SHA256:
- e244d4b2472f5d0fa60fd137f070cde59060f4ec8d7873ea3d4ebe456d428770
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.