Instructions to use Aditya2162/ivus-segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Aditya2162/ivus-segmentation with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Aditya2162/ivus-segmentation") - Notebooks
- Google Colab
- Kaggle
File size: 282 Bytes
1d197a4 | 1 2 3 4 5 6 7 8 | import tensorflow as tf
m = tf.saved_model.load("./model")
print("Has call:", callable(m))
print("Num variables:", len(getattr(m, "variables", [])))
print("Num trainable:", len(getattr(m, "trainable_variables", [])))
print("Signatures:", list(getattr(m, "signatures", {}).keys()))
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