Instructions to use apple/DepthPro-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apple/DepthPro-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="apple/DepthPro-hf")# Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("apple/DepthPro-hf") model = AutoModelForDepthEstimation.from_pretrained("apple/DepthPro-hf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from apple/DepthPro-hf: direct link, hf CLI and curl.
- Browser
- Download file 1.9 GB
-
https://huggingface.co/apple/DepthPro-hf/resolve/main/model.safetensors
- Command line
-
hf download hf://apple/DepthPro-hf/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/apple/DepthPro-hf/resolve/main/model.safetensors
1.9 GB
- Xet hash:
- 82588f2a9e506f3ec4983e504fd7cd2c08f9e24e8de15d79c6df42026cb31611
- Size of remote file:
- 1.9 GB
- SHA256:
- 9c6811e3165485b9a94a204329860cb333a79877e757eb795a179a4ea34bbcf7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.