Instructions to use IDEA-CCNL/Erlangshen-MacBERT-325M-TextMatch-Chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IDEA-CCNL/Erlangshen-MacBERT-325M-TextMatch-Chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="IDEA-CCNL/Erlangshen-MacBERT-325M-TextMatch-Chinese")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("IDEA-CCNL/Erlangshen-MacBERT-325M-TextMatch-Chinese") model = AutoModelForMaskedLM.from_pretrained("IDEA-CCNL/Erlangshen-MacBERT-325M-TextMatch-Chinese") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4c84c333eca9e31e1326418eca4c8c0ea6af8661033b71a0d7bc6227c7e7b21
- Size of remote file:
- 1.3 GB
- SHA256:
- 5c2be0278e9501b60d83e2c9864564d622e11b29101aa495daeb37f1f9c43d36
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