Instructions to use keja/deeplab-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use keja/deeplab-v3 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://keja/deeplab-v3") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 05134ba4d952110811bc49890ef63bf91d4c843a53b1a5444a196b6f720186be
- Size of remote file:
- 798 kB
- SHA256:
- 48edc56bd25560e5e78d0379fba052e1afb6db089a7fcab3c917bdc40ee7f6c0
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