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:
- 118de7c4b5e3a626e82bb9ac7273e238de1d7bacf46e50db404e5bc15b5882e0
- Size of remote file:
- 3.06 kB
- SHA256:
- c01df3797d2d805016e73fc5593aa38cf26500df46e15acf25b1227fc81138f5
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