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:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://keja/deeplab-v3") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from keja/deeplab-v3: direct link, hf CLI and curl.
- Browser
- Download file 2.84 MB
-
https://huggingface.co/keja/deeplab-v3/resolve/main/saved_model.pb
- Command line
-
hf download hf://keja/deeplab-v3/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/keja/deeplab-v3/resolve/main/saved_model.pb
2.84 MB
- Xet hash:
- b42c84ea6a21488945d1286464922745178865a404d64bee4a87f5a409e3a0d5
- Size of remote file:
- 2.84 MB
- SHA256:
- 8f55d033cdbb371cb7cee0a5d5098655eee809a696c2ab7d387455976d9a72c0
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