# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("castorini/monot5-large-msmarco")
model = AutoModel.from_pretrained("castorini/monot5-large-msmarco", device_map="auto")Quick Links
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
This model is a T5-large reranker fine-tuned on the MS MARCO passage dataset for 100k steps (or 10 epochs).
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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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="castorini/monot5-large-msmarco")