Instructions to use aimarsg/ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aimarsg/ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="aimarsg/ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("aimarsg/ner") model = AutoModelForTokenClassification.from_pretrained("aimarsg/ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aca300e2cf99f7068e9a4934492f21e88559984bd69f69742fff45c2e26870aa
- Size of remote file:
- 496 MB
- SHA256:
- 09e3fd2069f8514b36783b1395d9b6c014a4af2a68ab868eb2d0f8dcf9413ed8
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