Instructions to use hf-internal-testing/tiny-random-BeitBackbone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BeitBackbone with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, BeitBackbone processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-BeitBackbone") model = BeitBackbone.from_pretrained("hf-internal-testing/tiny-random-BeitBackbone", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-BeitBackbone: direct link, hf CLI and curl.
- Browser
- Download file 118 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-BeitBackbone/resolve/refs%2Fpr%2F50/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-BeitBackbone@refs/pr/50/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-BeitBackbone/resolve/refs%2Fpr%2F50/model.safetensors
118 kB
- Xet hash:
- c31a659726f9063fa4dcc68ea356ca3d37d862279a7d8f216e05c61b78a00558
- Size of remote file:
- 118 kB
- SHA256:
- 8063c05acc2f4c258917f1d99f22cb79168a46e52163951df89c844e9150191c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.