Instructions to use hf-internal-testing/tiny-random-FocalNetForMaskedImageModeling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FocalNetForMaskedImageModeling with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, FocalNetForMaskedImageModeling processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-FocalNetForMaskedImageModeling") model = FocalNetForMaskedImageModeling.from_pretrained("hf-internal-testing/tiny-random-FocalNetForMaskedImageModeling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-FocalNetForMaskedImageModeling: direct link, hf CLI and curl.
- Browser
- Download file 353 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-FocalNetForMaskedImageModeling/resolve/dd58b2d91537e5b47b9e7aa91111d5fe3303c95c/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-FocalNetForMaskedImageModeling@dd58b2d91537e5b47b9e7aa91111d5fe3303c95c/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-FocalNetForMaskedImageModeling/resolve/dd58b2d91537e5b47b9e7aa91111d5fe3303c95c/pytorch_model.bin
353 kB
- Xet hash:
- d276796ab6aac791eeddb46a515f75a3b6277091fd9d0950a263ca9d3969e870
- Size of remote file:
- 353 kB
- SHA256:
- fc96fd0999c06e47763215c371d9b22483bc82df39835c0e99253d6a9b7a6846
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