Instructions to use m1969m/bert-base-cased-sci-units-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m1969m/bert-base-cased-sci-units-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="m1969m/bert-base-cased-sci-units-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("m1969m/bert-base-cased-sci-units-ner") model = AutoModelForTokenClassification.from_pretrained("m1969m/bert-base-cased-sci-units-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 394fa6aff942b78752f1148c1321ff1ef0f0b60e7431732e6add51660f012966
- Size of remote file:
- 5.2 kB
- SHA256:
- 5a3a589528d66043f7f97aac2b4c6e048c40c2788fce8f9fd6c1ef3ed4df26a4
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