Instructions to use pstroe/roberta-base-latin-cased3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pstroe/roberta-base-latin-cased3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pstroe/roberta-base-latin-cased3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pstroe/roberta-base-latin-cased3") model = AutoModelForMaskedLM.from_pretrained("pstroe/roberta-base-latin-cased3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89ff3392e66b3548bd1f67477bb42924ae41a26af08febcfe7a6be0415ff1d3e
- Size of remote file:
- 891 MB
- SHA256:
- 7704f65f6be4f22189f404cfc378ac46cf87be5ed2c50be8a32d839fb68982c9
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