Instructions to use Roy229/nml7324-ner-tagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Roy229/nml7324-ner-tagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Roy229/nml7324-ner-tagger")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Roy229/nml7324-ner-tagger", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Named Entity Recognition Tagger
Extracts organisations, people and locations from unstructured legal documents. Used by the contracts team to automate clause indexing and obligation tracking. The model is fine-tuned from a multilingual encoder and currently covers English, French and German legal text with an F1 score above 0.92 on the internal evaluation set.
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