Instructions to use hf-internal-testing/tiny-random-PoolFormerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PoolFormerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-PoolFormerModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-PoolFormerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-PoolFormerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20bc7ce8654415a7467a43b81bfe9303cb528c8baeb6e332c6f9befe76ca145b
- Size of remote file:
- 1.82 MB
- SHA256:
- c90173c01c604b7f1dc332c2d458e8847b042d290af49b10250b69e83f30250f
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