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:
- 685d238ef2ee1efa22af4452b2caf9f6a8baa14045b0d9f13b2a93fa8866c0ee
- Size of remote file:
- 39.5 kB
- SHA256:
- 4aa4509ef4b7dfa71cea5cc24d77c2d02d55d71d5fd1a3b6b4cd933108e849da
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