Instructions to use IDEA-CCNL/Erlangshen-DeBERTa-v2-97M-CWS-Chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IDEA-CCNL/Erlangshen-DeBERTa-v2-97M-CWS-Chinese with Transformers:
# Load model directly from transformers import AutoTokenizer, BertSoftmaxForNer tokenizer = AutoTokenizer.from_pretrained("IDEA-CCNL/Erlangshen-DeBERTa-v2-97M-CWS-Chinese") model = BertSoftmaxForNer.from_pretrained("IDEA-CCNL/Erlangshen-DeBERTa-v2-97M-CWS-Chinese") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e9426ad310848df16144a21a4ada9903e21b0cdf06db7fbe6e584c014cdff35
- Size of remote file:
- 388 MB
- SHA256:
- 3676bba9d801cfc4f183ac5943110c2a4f3e03de8c993376230ac95ca3ca9d77
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.