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%2F71/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-BeitBackbone@refs/pr/71/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-BeitBackbone/resolve/refs%2Fpr%2F71/model.safetensors
118 kB
- Xet hash:
- 0e39c57886513f135b5c2833bd15829641f57ff3a58c0fcd43fb05a3df59913e
- Size of remote file:
- 118 kB
- SHA256:
- 6f6e455f634de99e04817110ebb6cf733bd8426f03b72a25220b0666013d24e5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.