Instructions to use hf-internal-testing/tiny-random-clip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-clip with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-clip", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e82f44ef6eef87c1bf19eb197fdd0377b64d7a1cb41bbae061c5e227eb74aa46
- Size of remote file:
- 6.71 MB
- SHA256:
- fd463d8581f5032d0cc194068b4b8e05d5489b4b8478ca92368bac42d8ad4a48
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.