Fill-Mask
Transformers
PyTorch
luke
named entity recognition
relation classification
question answering
Instructions to use studio-ousia/mluke-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use studio-ousia/mluke-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="studio-ousia/mluke-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("studio-ousia/mluke-base") model = AutoModelForMaskedLM.from_pretrained("studio-ousia/mluke-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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- Update README.md (b6fd903de9f5c4889163446305beb962e3e2f480) Co-authored-by: Loïck BOURDOIS <lbourdois@users.noreply.huggingface.co>39eaaef
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