Instructions to use IDEA-CCNL/Erlangshen-TCBert-110M-Classification-Chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IDEA-CCNL/Erlangshen-TCBert-110M-Classification-Chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="IDEA-CCNL/Erlangshen-TCBert-110M-Classification-Chinese")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("IDEA-CCNL/Erlangshen-TCBert-110M-Classification-Chinese") model = AutoModelForMaskedLM.from_pretrained("IDEA-CCNL/Erlangshen-TCBert-110M-Classification-Chinese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86f694de41f7a251584b26cd1276ce56f384e64f719f47d5d338ec6ec44a5ae9
- Size of remote file:
- 477 MB
- SHA256:
- cefaf0050bb59815c5d967884864435c5017c7cb37dfb4fbd85a6740db397675
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