Instructions to use OpenMatch/cocodr-base-msmarco-warmup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMatch/cocodr-base-msmarco-warmup with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="OpenMatch/cocodr-base-msmarco-warmup")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("OpenMatch/cocodr-base-msmarco-warmup") model = AutoModelForMaskedLM.from_pretrained("OpenMatch/cocodr-base-msmarco-warmup") - Notebooks
- Google Colab
- Kaggle
license: mit
This model has been pretrained on BEIR corpus then finetuned on MS MARCO with BM25 warmup only, 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.
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