Fill-Mask
Transformers
Safetensors
English
roberta
law
legal
australia
Generated from Trainer
feature-extraction
Eval Results (legacy)
Instructions to use isaacus/emubert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use isaacus/emubert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="isaacus/emubert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("isaacus/emubert") model = AutoModelForMaskedLM.from_pretrained("isaacus/emubert") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- bbd626d03142c62318c9b770d9a346fd07e4267f41b6703a72beca541eb0b182
- Size of remote file:
- 1.5 MB
- SHA256:
- df1df525e97298d1342318098919ef74b17764321e05ca85c0ce92d7268f52f8
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