Reinforcement Learning
Keras
English
tensoraerospace
control
ihdp
aerospace
f16
gymnasium
tensorflow
Eval Results (legacy)
Instructions to use TensorAeroSpace/ihdp-f16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use TensorAeroSpace/ihdp-f16 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://TensorAeroSpace/ihdp-f16") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb959e86575ae12df695a6ac35fbd60cfa3ff3c073bd6d49e0456ea827b41f1a
- Size of remote file:
- 13.9 kB
- SHA256:
- 11a676698e34c0a5e8104babe7fad2fd1900c4618cd355b986c9543a45735f3f
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