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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b64ba6a002d0e293650da7f923bf594e4641e47d3b31bb14ee948e232fe86b0
- Size of remote file:
- 47.9 MB
- SHA256:
- f54c3cc4d0095d8565cd67168f248799c6313a84f575a24ed3ea4b7ba0920427
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