Instructions to use hf-tiny-model-private/tiny-random-Mask2FormerModel 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-Mask2FormerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-Mask2FormerModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-Mask2FormerModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-Mask2FormerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bddce9dfcfaa31f2baaf4bc0b126c216efb353576dfb5c2f5f61f4729adbea1b
- Size of remote file:
- 47.3 MB
- SHA256:
- d5b4bf2be620c5530a2b5099bbc82de95888bf3e1abcc06e7dcbab251fcc2178
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