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:
- 3b3e9c33fc2dec72b36d6faee857fa56980904e007421a031eddd293b4e3d4de
- Size of remote file:
- 32.1 MB
- SHA256:
- b2c4292bd8161f6a004cda023619796e7ff3759c81772c827c14c6c4648c6a9e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.