Instructions to use OpenMatch/cocodr-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMatch/cocodr-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="OpenMatch/cocodr-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("OpenMatch/cocodr-base") model = AutoModelForMaskedLM.from_pretrained("OpenMatch/cocodr-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| This model has been pretrained on BEIR corpus without relevance-level supervision following the approach described in the paper **COCO-DR: Combating Distribution Shifts in Zero-Shot Dense Retrieval with Contrastive and Distributionally Robust Learning**. The associated GitHub repository is available here https://github.com/OpenMatch/COCO-DR. | |
| This model is trained with BERT-base as the backbone with 110M hyperparameters. | |
| license: mit | |
| --- | |