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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d3cafb7dc606a9546afcc68b84af44dde871689ab82db79dfbc60e5577463c4
- Size of remote file:
- 1.85 MB
- SHA256:
- df405966b2f8be955891bea6a1bd65da52956a4183ea37479f6073c89fd35294
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