Instructions to use hf-internal-testing/tiny-random-UMT5EncoderModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UMT5EncoderModel with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-UMT5EncoderModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-UMT5EncoderModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 221841a3255e5464543d40b3c4ba207a03ed5699100876557fd06dc4320159f3
- Size of remote file:
- 33.1 MB
- SHA256:
- 511f684ee79fb00710bc29fe4e6ab4d91c64dfc0ebfa44452b2e19ca36427ad6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.