Instructions to use MiDRASH-ERC/JABERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MiDRASH-ERC/JABERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MiDRASH-ERC/JABERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MiDRASH-ERC/JABERT") model = AutoModelForMaskedLM.from_pretrained("MiDRASH-ERC/JABERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d046b2fc653e653871c60cf65ac086908957bd9c0654a719c6e522376b77bfab
- Size of remote file:
- 738 MB
- SHA256:
- cefe9c1d3bbe6417fa7a268561d69e9302e4674814408a97a5e17bf12cb8e3ab
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