Instructions to use hf-internal-testing/tiny-random-Mask2FormerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Mask2FormerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-Mask2FormerModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-Mask2FormerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-Mask2FormerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87106739b3df803878bf3a6b909d7b05d05aed726572c23fcaaf1c877c4643e7
- Size of remote file:
- 47.3 MB
- SHA256:
- 1e84295afd0a89bf3e56fc5673975950a019c32d5c59e7198a78f76559b3f285
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