Instructions to use hf-internal-testing/tiny-random-OneFormerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-OneFormerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-OneFormerModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-OneFormerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-OneFormerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1087fe1923aab7ef4c941fd20d7c68b391ef9f75ccd6b8d6e1c3309635aea336
- Size of remote file:
- 47.8 MB
- SHA256:
- eaf5e8142f3167f516eeb8d45f25e1fca0e0c013a6f743d53cf7d7ed4436bd45
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