Instructions to use up201806461/bert-java-bfp_single with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use up201806461/bert-java-bfp_single with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="up201806461/bert-java-bfp_single")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("up201806461/bert-java-bfp_single") model = AutoModelForMaskedLM.from_pretrained("up201806461/bert-java-bfp_single") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c71407ebaace0d204b086f86f082a6c41476d6551b9f20a4517a04fa31fdcfdc
- Size of remote file:
- 433 MB
- SHA256:
- c72018439bb796a02a21bcfe9cfd5fe73ca2ed3293bd94985008c932ca4c4a39
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