Instructions to use hf-internal-testing/tiny-random-MT5EncoderModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MT5EncoderModel with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MT5EncoderModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MT5EncoderModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b9fffd7021cc94d760715a789b32e2633bc72bb8599b359dbc38179ec0ddeb1
- Size of remote file:
- 64.1 MB
- SHA256:
- c3d67f5d86ef7b2ecf91f93e4b3ee72693dfff7995b60112ab1b7d1ad90d668b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.