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")# 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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36d211b7f56ac687c02a1f70cb4eee601bae029a2eb54f0a01e1881cd9bcd06c
- Size of remote file:
- 39.5 kB
- SHA256:
- b98e3e2c877c8439c9fd14d90a0375f1b8a99f1ae7d63ff124c3b7a10bdd6c05
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