Instructions to use hf-internal-testing/tiny-random-UdopModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UdopModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-UdopModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-UdopModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-UdopModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a29d82dc8caf5a40f011f9a8f62d24e8d6e64c4c576f853c53551fe00576d0e
- Size of remote file:
- 4.83 MB
- SHA256:
- 92920c4870144e3b0552d080e7b5bfcbe982c2f222da9b9d00c826239b452832
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.