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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7901545fa99aa2c6fc6e7dd5d52e137b007e88995cbc7a29393cc2ed5cb2e2fa
- Size of remote file:
- 440 MB
- SHA256:
- 0fc9c885d3ff7e51c57dfdfb94bbf049fae2042d0b01fdd40684e68afab2cced
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