Instructions to use Intel/dpt-beit-large-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/dpt-beit-large-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="Intel/dpt-beit-large-384")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("Intel/dpt-beit-large-384") model = AutoModelForDepthEstimation.from_pretrained("Intel/dpt-beit-large-384", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md (#4)
Verified signature- Update README.md (2811c0ab660bb3bd38b5a431bd7e6a34cc9671e8) Co-authored-by: bob chesebrough <Chesebrough@users.noreply.huggingface.co>2f1cf99
-
Update Readme (#3)
Verified signature- Update Readme (60ae5f3828c8d7f854f963a35db40a2bc45dfe65) Co-authored-by: bob chesebrough <Chesebrough@users.noreply.huggingface.co>cea2081
-
Update preprocessor_config.json
29da776
-
Create README.md (#1)
- Create README.md (9109429c8a29c8f8421a5f6eb6413dbd6109ee7e)2cdaf85 -
Upload processor
629c7bd -
Upload DPTForDepthEstimation
a017ea5 -
initial commit
8729b14