Instructions to use macavaney/monot5-base-msmarco-sim5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use macavaney/monot5-base-msmarco-sim5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("macavaney/monot5-base-msmarco-sim5") model = AutoModelForMultimodalLM.from_pretrained("macavaney/monot5-base-msmarco-sim5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38dab9adb077f558bd793e608889b14ecf2dfd17ee98e2a3dd972e588006c3d0
- Size of remote file:
- 892 MB
- SHA256:
- 222ef712a091f56ef3a12c8687136793b028e0bc8c1a77e1b7298dd36fe6c257
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