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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12569154186a6dd627aaca1df77cf7ce266d12095c007d1d37b5b7f4ba325ef7
- Size of remote file:
- 64.1 MB
- SHA256:
- 1e78323060b588d1d2e7c7707aab6938d241909987fe1972954a1217fd4a2c1c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.