Instructions to use sergiopaniego/OptimizedPilotNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use sergiopaniego/OptimizedPilotNet with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("sergiopaniego/OptimizedPilotNet") - Notebooks
- Google Colab
- Kaggle
Download tensorflow/pilotnet_cqat_model.tflite from sergiopaniego/OptimizedPilotNet: direct link, hf CLI and curl.
- Browser
- Download file 1.62 MB
-
https://huggingface.co/sergiopaniego/OptimizedPilotNet/resolve/main/tensorflow/pilotnet_cqat_model.tflite
- Command line
-
hf download hf://sergiopaniego/OptimizedPilotNet/tensorflow/pilotnet_cqat_model.tflite
-
curl -L -o pilotnet_cqat_model.tflite https://huggingface.co/sergiopaniego/OptimizedPilotNet/resolve/main/tensorflow/pilotnet_cqat_model.tflite
1.62 MB
- Xet hash:
- 32dc581a421c4021b2e26b0ffb6db418ca6a0155d6dedd3d8e09fa8c4d1433ff
- Size of remote file:
- 1.62 MB
- SHA256:
- 83a8c02446082e9e5922eaa97804b650065a3587b301474c28b207225a1a95fe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.