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gov_law_clf_ner
sguarnaccio/gov_law_clf_ner
gov_law_clf_ner is a text classification model from sguarnaccio. Use it when you need a label for a piece of text. It is set up for transformers.
Model to predict and extract governing law from legal documents.
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Apr 13, 2023
- Updated
- Apr 13, 2023
- SHA
- 7b722981
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Model card
From the Hugging Face model README
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.
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")
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Apr 13, 2023
- Updated
- Apr 13, 2023