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
417a6c0 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%2F8/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-DepthAnythingForDepthEstimation@refs/pr/8/model.safetensors
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curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-DepthAnythingForDepthEstimation/resolve/refs%2Fpr%2F8/model.safetensors
39.5 kB
- Xet hash:
- 08ff2be86a67b85959379557d2cb20feb44017afe7db1c135785de441912966f
- Size of remote file:
- 39.5 kB
- SHA256:
- 98e6039449949146196b7134c22588eca67c15381254f9c48cd9a5ae672ba530
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