Instructions to use keetrap/Distill-Any-Depth-Small-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keetrap/Distill-Any-Depth-Small-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="keetrap/Distill-Any-Depth-Small-hf")# Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("keetrap/Distill-Any-Depth-Small-hf") model = AutoModelForDepthEstimation.from_pretrained("keetrap/Distill-Any-Depth-Small-hf") - Notebooks
- Google Colab
- Kaggle
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library_name: transformers
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tags:
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The original model belongs to: https://huggingface.co/xingyang1/Distill-Any-Depth.
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This will be deleted after the PR merge: https://github.com/huggingface/transformers/pull/36614
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library_name: transformers
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tags:
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- distil_any_depth
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- depth_estimation
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license: apache-2.0
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pipeline_tag: depth-estimation
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The original model belongs to: https://huggingface.co/xingyang1/Distill-Any-Depth.
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This will be deleted after the PR merge: https://github.com/huggingface/transformers/pull/36614
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