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
86efe85 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%2F10/model.safetensors
- Command line
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hf download hf://hf-internal-testing/tiny-random-DepthAnythingForDepthEstimation@refs/pr/10/model.safetensors
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curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-DepthAnythingForDepthEstimation/resolve/refs%2Fpr%2F10/model.safetensors
39.5 kB
- Xet hash:
- 30c9e994647f80fcbf638c60a1e218d788a1ba1c111a9648ef6ec233acb6d0ad
- Size of remote file:
- 39.5 kB
- SHA256:
- 5f26dbbc1a97efb1979c11e828fda3c4eca911954bf9ae1cd3ecbac7422333f6
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