Instructions to use DJF-on-arm/Iamam1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use DJF-on-arm/Iamam1 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://DJF-on-arm/Iamam1") - Notebooks
- Google Colab
- Kaggle
Create preRelease6/info.md
Browse files
versions/v1-x/v1.2.0-7M/preRelease6/info.md
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# Currently training on 18 epochs
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