Instructions to use logasja/FaceNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/FaceNet with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://logasja/FaceNet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6668af49bb61e9bc366c3d6d9819b24a219c3652da6396f5abfc38d98c0aa8bf
- Size of remote file:
- 92.4 MB
- SHA256:
- 4d5323ed8607578bb8d6be02059894efa538dd6669304ea30d8db6c89e72957d
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