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:
- a66ef049d44f0c59a5aff2e63e42f6aa725bd43fb09c7a2ad4f3cb86ac53576a
- Size of remote file:
- 12.3 MB
- SHA256:
- 492c3ff0e5ce222b1242494941c09c2d64a848c9a676bf59adc73a8ac4d33ae3
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