Instructions to use hf-tiny-model-private/tiny-random-DPTForDepthEstimation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-DPTForDepthEstimation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="hf-tiny-model-private/tiny-random-DPTForDepthEstimation")# Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-DPTForDepthEstimation") model = AutoModelForDepthEstimation.from_pretrained("hf-tiny-model-private/tiny-random-DPTForDepthEstimation") - Notebooks
- Google Colab
- Kaggle
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