Instructions to use DarthReca/depth-any-canopy-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DarthReca/depth-any-canopy-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="DarthReca/depth-any-canopy-small")# Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("DarthReca/depth-any-canopy-small") model = AutoModelForDepthEstimation.from_pretrained("DarthReca/depth-any-canopy-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b962ea31cce4c21322713f3659190075fdeef38a70edc770adb16c96226b20b7
- Size of remote file:
- 99.2 MB
- SHA256:
- e3fb96ab05574c6a70342b1cfd3d0848c2b96eba1cdcdbdfea7fe9ae549a2127
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.