Instructions to use LiheYoung/depth_anything_vitl14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LiheYoung/depth_anything_vitl14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="LiheYoung/depth_anything_vitl14")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("LiheYoung/depth_anything_vitl14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Push model using huggingface_hub.
Browse files- config.json +1 -0
- pytorch_model.bin +3 -0
config.json
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{"encoder": "vitl", "features": 256, "out_channels": [256, 512, 1024, 1024], "use_bn": false, "use_clstoken": false}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:6fda5199f0043e91e1c6117df00313db57c630d8ed0306070b43da1ecfffbd9d
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size 1341418857
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