Instructions to use a6047425318/room-3d-scene-estimation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use a6047425318/room-3d-scene-estimation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="a6047425318/room-3d-scene-estimation")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("a6047425318/room-3d-scene-estimation") model = AutoModelForDepthEstimation.from_pretrained("a6047425318/room-3d-scene-estimation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from a6047425318/room-3d-scene-estimation: direct link, hf CLI and curl.
- Browser
- Download file 245 MB
-
https://huggingface.co/a6047425318/room-3d-scene-estimation/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://a6047425318/room-3d-scene-estimation/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/a6047425318/room-3d-scene-estimation/resolve/main/pytorch_model.bin
245 MB
- Xet hash:
- 6cf6d0c642c59c50e9ddb20b7f95dacec69692330ddca81732ed55340c81efbe
- Size of remote file:
- 245 MB
- SHA256:
- c353b12e5f4e5fafd0053d1c19bf60dfb1562b74db4728c6920a2cf44782b603
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