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:
- 9b7e958183f7541a1ce3af8344c10b0613eac0ddd03056c5bfcab010dd231d94
- Size of remote file:
- 4.8 MB
- SHA256:
- 2841bd2acc6e960f6035dab1cb8a130802e61b840762d0fbefda37a62c02d5d4
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