Instructions to use dbernsohn/roberta-java with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbernsohn/roberta-java with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dbernsohn/roberta-java")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dbernsohn/roberta-java") model = AutoModelForMaskedLM.from_pretrained("dbernsohn/roberta-java") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 939859b3f7976bf3467d3461cdeec4831d1f6e52380414f017428a746f994b90
- Size of remote file:
- 334 MB
- SHA256:
- 332eea67fdc9af6c193a9247dd9d0fa2d9ad4c3ce75efba1841d714f4fbf84d9
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