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--- |
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language: |
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- en |
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metrics: |
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- accuracy |
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- seqeval |
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pipeline_tag: text-classification |
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tags: |
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- legal |
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--- |
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# Model Card for Model ID |
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<!-- Provide a quick summary of what the model is/does. --> |
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Model to predict and extract governing law from legal documents. |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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- **Developed by:** Sean Guarnaccio |
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- **Model type:** Text Classification/NER |
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- **Language(s) (NLP):** Pytorch |
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- **License:** [More Information Needed] |
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- **Finetuned from model [optional]:** nlpaueb/bert-base-uncased-contracts |
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### Direct Use |
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Identify the section of a legal contract that contains the governing law and extract then extract the value. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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```python |
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from transformers import AutoTokenizer |
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from clf_ner import ClassifierNER |
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tokenizer = AutoTokenizer.from_pretrained("sguarnaccio/gov_law_clf_ner") |
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model = ClassifierNER.from_pretrained("sguarnaccio/gov_law_clf_ner") |
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model.predict("This agreement shall be governed by the laws of the State of New Jersey") |
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``` |
