Instructions to use castorini/monot5-base-msmarco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use castorini/monot5-base-msmarco with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("castorini/monot5-base-msmarco") model = AutoModelForSeq2SeqLM.from_pretrained("castorini/monot5-base-msmarco", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6543b26fe30dc494f1d05f4d2c15c694d879baf29aba62e805e0215c0d329d21
- Size of remote file:
- 892 MB
- SHA256:
- 64467f69fc891a29b35b386b7d66e4a3cdb2285588dcc85b56c396eb3a31b398
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