Instructions to use joyebright/EAMT2023-EN-DE-DAG1-WithTAG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joyebright/EAMT2023-EN-DE-DAG1-WithTAG with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("joyebright/EAMT2023-EN-DE-DAG1-WithTAG", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9aeb3affeaea7cdc8a8ef85b1bb53cabe1c2048ecf82d6c9d9901804c531005c
- Size of remote file:
- 852 Bytes
- SHA256:
- 229593c10dbbdde527fc348feb0d88654760a67e68f68d9ad109286f5ab7b30e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.