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:
- 921b36f79f526e014ff9bf7b4d504ea6b2c2330fd7cc8df5ac2a8aa81c323ae8
- Size of remote file:
- 1.84 MB
- SHA256:
- 80cb59622732e3b0a9ccdd4468d29d59c25d8d40b42d77e053f83230244e40bd
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