Instructions to use twnlp/chinese-macbert-base-similarity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use twnlp/chinese-macbert-base-similarity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="twnlp/chinese-macbert-base-similarity")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("twnlp/chinese-macbert-base-similarity") model = AutoModelForMaskedLM.from_pretrained("twnlp/chinese-macbert-base-similarity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
MacBERT is an improved BERT with novel MLM as correction pre-training task, which mitigates the discrepancy of pre-training and fine-tuning.Retrain on a large Chinese matching dataset.
- Downloads last month
- 16