Instructions to use jacklin/DeLADE-CLS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jacklin/DeLADE-CLS with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jacklin/DeLADE-CLS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
This model, DeLADE+[CLS], is trained by fusing neural lexical and semantic components in single transformer using DistilBERT as a backbone. A Dense Representation Framework for Lexical and Semantic Matching Sheng-Chieh Lin and Jimmy Lin.
You can find the usage of the model in our DHR repo: (1) Inference on MSMARCO Passage Ranking; (2) Inference on BEIR datasets.