Instructions to use dataguychill/VioMobileNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use dataguychill/VioMobileNet 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("dataguychill/VioMobileNet") - Notebooks
- Google Colab
- Kaggle
Download model/saved_model.pb from dataguychill/VioMobileNet: direct link, hf CLI and curl.
- Browser
- Download file 60.9 MB
-
https://huggingface.co/dataguychill/VioMobileNet/resolve/main/model/saved_model.pb
- Command line
-
hf download hf://dataguychill/VioMobileNet/model/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/dataguychill/VioMobileNet/resolve/main/model/saved_model.pb
60.9 MB
- Xet hash:
- 8c33f1be988c34ba7a4b81045bc21532e1ca9cacd0cff58755fa138729cb4dc2
- Size of remote file:
- 60.9 MB
- SHA256:
- 3489bbe631db94fd531e3315c4c0b9dc8b32d1427991d390a7fd6bd67d79f56b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.