Instructions to use AlbertiTechnology/MgO-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use AlbertiTechnology/MgO-v1 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://AlbertiTechnology/MgO-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e5cf4648e2d12a2e940f71377fcf40d87d49fb8f448184d30f39a320b2594f3
- Size of remote file:
- 23.3 MB
- SHA256:
- 6c011525fb00eba0ed42c80a18d016a45241459f30e10bfd9e0c488bb5514f66
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.