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:
- a98d42e2c03955a8f0df885837cacc384cafec14a63e1a2ee8bcf0771cfb402c
- Size of remote file:
- 32.1 MB
- SHA256:
- 7c828dc9b64dd0bbdecad4f75b3e9f69be4686854317dfd3f5d35228c2b2a3b0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.