Instructions to use romainhardy/ColonCrafter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use romainhardy/ColonCrafter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="romainhardy/ColonCrafter")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("romainhardy/ColonCrafter", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ceda3e133b4146f9560cf88564db033566fb447955c67aa35890070615ef43e
- Size of remote file:
- 4.54 GB
- SHA256:
- de0e71048aea005166abe658b1c7d1f2f21059d9630c03627740bd09d6e80f10
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