Instructions to use NLP4H/ms_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLP4H/ms_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NLP4H/ms_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NLP4H/ms_bert") model = AutoModelForMaskedLM.from_pretrained("NLP4H/ms_bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 643ea22c9085f0bc8ecd6c12a4d913f3ba8388602dd5eb33f726adb1b0a7dc08
- Size of remote file:
- 440 MB
- SHA256:
- b8b356856c0197b40ecabee9a9f9fc6d0be59dfcdce2184ed4a87b0315fa2c8a
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