Instructions to use hf-internal-testing/tiny-random-FocalNetBackbone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FocalNetBackbone with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, FocalNetBackbone processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-FocalNetBackbone") model = FocalNetBackbone.from_pretrained("hf-internal-testing/tiny-random-FocalNetBackbone", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-FocalNetBackbone: direct link, hf CLI and curl.
- Browser
- Download file 302 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-FocalNetBackbone/resolve/41f855e6d51cc77febb992d86cb3bfd2f04ef931/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-FocalNetBackbone@41f855e6d51cc77febb992d86cb3bfd2f04ef931/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-FocalNetBackbone/resolve/41f855e6d51cc77febb992d86cb3bfd2f04ef931/pytorch_model.bin
302 kB
- Xet hash:
- 9e5709e8466527221dbc5cc54176f81b84810abd9c79b297fe522e269bd31bda
- Size of remote file:
- 302 kB
- SHA256:
- 518c5f2b09e3e0d9a3616a740b373a9130d092a95b5e7ca5665ae3055d16f7ac
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