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:
- 74188c5824e60502df567e0baa13d7c631c19347d622af7ace05dba3133149c8
- Size of remote file:
- 64.1 MB
- SHA256:
- c4a0fd40d4fb52efe2d06e4c02111bded778e03e5c1a1cfb293a794c141f23ea
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.