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")# pip install -U transformers accelerate # 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
Download model.safetensors from hf-internal-testing/tiny-random-PoolFormerModel: direct link, hf CLI and curl.
- Browser
- Download file 1.82 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-PoolFormerModel/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-PoolFormerModel@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-PoolFormerModel/resolve/refs%2Fpr%2F1/model.safetensors
1.82 MB
- Xet hash:
- 20bc7ce8654415a7467a43b81bfe9303cb528c8baeb6e332c6f9befe76ca145b
- Size of remote file:
- 1.82 MB
- SHA256:
- c90173c01c604b7f1dc332c2d458e8847b042d290af49b10250b69e83f30250f
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