---
language:
- en
metrics:
- accuracy
- seqeval
pipeline_tag: text-classification
tags:
- legal
---
# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->

Model to predict and extract governing law from legal documents.

## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

- **Developed by:** Sean Guarnaccio
- **Model type:** Text Classification/NER
- **Language(s) (NLP):** Pytorch
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** nlpaueb/bert-base-uncased-contracts

### Direct Use

Identify the section of a legal contract that contains the governing law and extract then extract the value.
## How to Get Started with the Model

Use the code below to get started with the model.
```python
from transformers import AutoTokenizer
from clf_ner import ClassifierNER

tokenizer = AutoTokenizer.from_pretrained("sguarnaccio/gov_law_clf_ner")

model = ClassifierNER.from_pretrained("sguarnaccio/gov_law_clf_ner")
model.predict("This agreement shall be governed by the laws of the State of New Jersey")
```