Instructions to use castorini/monot5-base-msmarco-10k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use castorini/monot5-base-msmarco-10k with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("castorini/monot5-base-msmarco-10k") model = AutoModelForSeq2SeqLM.from_pretrained("castorini/monot5-base-msmarco-10k") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
This model is a T5-base reranker fine-tuned on the MS MARCO passage dataset for 10k steps (or 1 epoch).
This model usually has a better zero-shot performance than monot5-base-msmarco, i.e., it performs better on datasets different from MS MARCO.
For more details on how to use it, check the following links:
Paper describing the model: Document Ranking with a Pretrained Sequence-to-Sequence Model
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