Instructions to use CAUKiel/JavaBERT-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CAUKiel/JavaBERT-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="CAUKiel/JavaBERT-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("CAUKiel/JavaBERT-uncased") model = AutoModelForMaskedLM.from_pretrained("CAUKiel/JavaBERT-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eaeedc88a0414d1d9ed4c273216d1963280356d0c38f7116e67f84567e14e1f5
- Size of remote file:
- 438 MB
- SHA256:
- 65385aa6a4acc9770231945a3a3759ff4b3b1841bd74223dcc45b29c677d0aca
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