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:
- b7cafa6806958b491414f4bc1a4a2cddc5afc980d0640c862c000692b57235de
- Size of remote file:
- 334 MB
- SHA256:
- 2179fecbc29d4752bc42c6000d2714d538e5adc495f4d69ecd94a8eac489dff0
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