Instructions to use hf-internal-testing/tiny-random-beit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-beit with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-beit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cec27ba2ee62e404cfd01819d097b4554e15f567d5b8f369ce66384d00f91ad4
- Size of remote file:
- 167 kB
- SHA256:
- 0a3df7348a9a4b895daa2c7fedb8360a124d6fabc891357d794e0a55cae0c564
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.