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:
- f25481e3b06eb336529b3eefdd9bdfdc2c5a93076c5a7384d8bfe2e9bebef760
- Size of remote file:
- 438 MB
- SHA256:
- 067413645eab755f04630f4e27d1b93c06aada02b0699f784ed271a46b119723
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