Instructions to use zeromodels/tf_efficientnetv2_m_in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use zeromodels/tf_efficientnetv2_m_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_m_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_m_in1k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e66d65ac963ed881393e042e8c67b700c904d7b041c596b51f28edc2005abc83
- Size of remote file:
- 220 MB
- SHA256:
- e2a583151231cd958f08cc118eee7882bed83d31cc6f69001ff3c7ff53926b06
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