Instructions to use studio-ousia/luke-base-lite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use studio-ousia/luke-base-lite with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="studio-ousia/luke-base-lite")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("studio-ousia/luke-base-lite") model = AutoModelForMaskedLM.from_pretrained("studio-ousia/luke-base-lite") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bcbbb890b8340468cd88d5abf82a61ffe552d2089bf3143fb8e32c45f3a463bc
- Size of remote file:
- 589 MB
- SHA256:
- 01b47daa243cba92b271d206ab443a5fc6b78e7a3bb040da8a9a175118e331b0
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