Instructions to use zeromodels/tf_efficientnetv2_b0_in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use zeromodels/tf_efficientnetv2_b0_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_efficientnetv2_b0_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_efficientnetv2_b0_in1k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9c9533c5b9ff0e113ea093b15877a7c9f711054fea2a260658b278f0022b45e
- Size of remote file:
- 29.5 MB
- SHA256:
- 06811388b37af59b5409dbc6ad020b8c9e65462692491f72d3fb625074f1ec91
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.