Instructions to use Intel/dpt-hybrid-midas with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/dpt-hybrid-midas with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="Intel/dpt-hybrid-midas")# Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("Intel/dpt-hybrid-midas") model = AutoModelForDepthEstimation.from_pretrained("Intel/dpt-hybrid-midas", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Intel/dpt-hybrid-midas: direct link, hf CLI and curl.
- Browser
- Download file 490 MB
-
https://huggingface.co/Intel/dpt-hybrid-midas/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Intel/dpt-hybrid-midas/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Intel/dpt-hybrid-midas/resolve/main/pytorch_model.bin
490 MB
- Xet hash:
- 38ed955c8797676ee30b8643e6c2e5c65a78baefe5a0a5408eeb2ce450c35633
- Size of remote file:
- 490 MB
- SHA256:
- b6c4d44f9d96ca3fa76dd3bbb153989a60b4ad5526559f3c598562a368d687ec
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