Instructions to use studiolike/cap_01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use studiolike/cap_01 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://studiolike/cap_01") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a3aa943e10158c2aac0e1d7a39cf47ee02d59f633cd89f30f95adf9c00eef2d
- Size of remote file:
- 38.7 kB
- SHA256:
- 0fe34bd23a0df6bd53e9fe8f103f7dee2af4c7dab9f6db011b909ac112b41f8b
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