Instructions to use ClassCat/roberta-base-latin-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ClassCat/roberta-base-latin-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ClassCat/roberta-base-latin-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ClassCat/roberta-base-latin-v2") model = AutoModelForMaskedLM.from_pretrained("ClassCat/roberta-base-latin-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 520af3aa3a2db770abdb674bb4a04bcfde560a3659934f30644c45651696e906
- Size of remote file:
- 498 MB
- SHA256:
- 79048bdbde2c7b3454eac84050b4c0340c84db49f938f7311c076b29cccb13de
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