Instructions to use olm/olm-roberta-base-oct-2022 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use olm/olm-roberta-base-oct-2022 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="olm/olm-roberta-base-oct-2022")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("olm/olm-roberta-base-oct-2022") model = AutoModelForMaskedLM.from_pretrained("olm/olm-roberta-base-oct-2022") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13c6ba2f5ce0326b057eb6f54a4aa2f32d7cdb4bf9ca0a41566d925f440fe7e5
- Size of remote file:
- 499 MB
- SHA256:
- e79455317e33870e34d11f917be4eff1983416c0a2dab93550055b8ce1ed3dbc
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