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:
- 368953bcf9a75ef5992e3ec27021ab9ae8a7cdfa2a57bc7c076717fa63d37070
- Size of remote file:
- 32.1 MB
- SHA256:
- 95d4683c886daf5a2cce0005514f02c5e29ca6026959fa3bc537feb04238c8ca
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.