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
Upload tokenizer.pkl
Browse files
versions/v1-x/v1.2.0-7M/preRelease5/tokenizer.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:703f936967a23cfbe7a076bf123de0b25c84760cfdf422efe649e976b2d075d6
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size 6369090
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