Keras
LiteRT
tensorflow
tensorflow-lite
int8
quantization
edge-ai
embedded-ml
radar
sensor-data
hyperparameter-tuning
Instructions to use enesor0/pulsar-radar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use enesor0/pulsar-radar with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://enesor0/pulsar-radar") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 359079efbfd5fa5f7d0944c06b27ef38c6573d166e76ee69a7c65df9ae8aa38c
- Size of remote file:
- 135 kB
- SHA256:
- fbf6f701475ecf0f5a067442c4234cb3a2d38c712383da959e92917af1e4a835
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