Instructions to use reaprtripr/pretrained_java_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reaprtripr/pretrained_java_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="reaprtripr/pretrained_java_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("reaprtripr/pretrained_java_bert") model = AutoModelForMaskedLM.from_pretrained("reaprtripr/pretrained_java_bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e8f33cf8d86209cb7c7918eeef2e127d66a5b18f6835c39e16dc80078fff3044
- Size of remote file:
- 334 MB
- SHA256:
- 776c77acf17c28c57eb20e8a209b7be78767d89c7ec7e2b6608fe303b6a873f8
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