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:
- 38d8f22027b0dd492736e85208002b374ff7f8bc33d62178e3fd129f33866de8
- Size of remote file:
- 32.1 MB
- SHA256:
- e719e37b447cd849026c64bfc62390cc9ea8d257bd5541f8975a3e8007f81f42
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.