Instructions to use CAUKiel/JavaBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CAUKiel/JavaBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="CAUKiel/JavaBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("CAUKiel/JavaBERT") model = AutoModelForMaskedLM.from_pretrained("CAUKiel/JavaBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Added bibtex to the Model Card
Verified signatured40b176
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Adding `safetensors` variant of this model (#3)
- Adding `safetensors` variant of this model (b7e7cc77e97f81014a3ff87b93e9f43aa2b38ba0) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>bac399e
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model documentation (#2)
- model documentation (4e2edd99993fccdf5928d170acd3ff3d7eb44147) Co-authored-by: Nazneen Rajani <nazneen@users.noreply.huggingface.co>3b2ebe8
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Update README.md, removed java as language
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Modified widget text to reset its cache
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Added running model
Nelson Tavares de Sousaead5aab -
initial commit
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