Instructions to use hf-internal-testing/tiny-random-DinatBackbone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DinatBackbone with Transformers:
# Load model directly from transformers import AutoImageProcessor, DinatBackbone processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-DinatBackbone") model = DinatBackbone.from_pretrained("hf-internal-testing/tiny-random-DinatBackbone", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c6a597f04e342812db75dbcf7320d7272a80bb5fa7d72fbd5c850cf785896da
- Size of remote file:
- 339 kB
- SHA256:
- 3c11135f3d36670a923cf302751bd497f78187fad8e39a42be49b1a6110958c1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.