Instructions to use dslim/bert-base-NER-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dslim/bert-base-NER-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dslim/bert-base-NER-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dslim/bert-base-NER-uncased") model = AutoModelForTokenClassification.from_pretrained("dslim/bert-base-NER-uncased") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
905ef91 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:a553622c3b8cdd413cf4872ace1880ec6bbab3308a1847dd26cee7692a757dd6
size 438006919
|