Fill-Mask
Transformers
PyTorch
English
luke
named entity recognition
entity typing
relation classification
question answering
Instructions to use studio-ousia/luke-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use studio-ousia/luke-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="studio-ousia/luke-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("studio-ousia/luke-large") model = AutoModelForMaskedLM.from_pretrained("studio-ousia/luke-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1c3d05bba03205722110b19a8633c9456f735f54a8e7f11fb89963e2ebda056
- Size of remote file:
- 2.25 GB
- SHA256:
- 9ea73dbb7e0625e88c646f26230902c3df000e71320139e99b0703e1654f7bcc
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