Instructions to use camstack/camstack-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use camstack/camstack-models with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("camstack/camstack-models") - Notebooks
- Google Colab
- Kaggle
camstack-models / vehicleClassification /efficientnet /onnx /camstack-vehicle-type-efficientnet.onnx
Upload vehicleClassification/efficientnet/onnx/camstack-vehicle-type-efficientnet.onnx with huggingface_hub
e9faba7 verified - Xet hash:
- 83a589eb96af0ca7d04e2b9094c29a872a108bc2a2b8710b5af9dcd6a1997db3
- Size of remote file:
- 135 MB
- SHA256:
- 5faa03102e70f322b6171c6fc9e99f7cb58fc5ff98651827a2e7534208a4a9b6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.