Instructions to use hf-internal-testing/tiny-random-DepthAnythingForDepthEstimation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DepthAnythingForDepthEstimation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="hf-internal-testing/tiny-random-DepthAnythingForDepthEstimation")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-DepthAnythingForDepthEstimation") model = AutoModelForDepthEstimation.from_pretrained("hf-internal-testing/tiny-random-DepthAnythingForDepthEstimation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
hf-transformers-bot HF Staff
Update tiny models for DepthAnythingForDepthEstimation
46cb877 verified Download model.safetensors from hf-internal-testing/tiny-random-DepthAnythingForDepthEstimation: direct link, hf CLI and curl.
- Browser
- Download file 39.5 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-DepthAnythingForDepthEstimation/resolve/refs%2Fpr%2F72/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-DepthAnythingForDepthEstimation@refs/pr/72/model.safetensors
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curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-DepthAnythingForDepthEstimation/resolve/refs%2Fpr%2F72/model.safetensors
39.5 kB
- Xet hash:
- 541c11121a72b00d9fd2e2bb2478c7acc12c5d1df16557987ddbf668455d7165
- Size of remote file:
- 39.5 kB
- SHA256:
- 88892ebec3a5325a9014869845ab8c1e8737779cee6b4720b4fd64959df5c160
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