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---
title: Hackathon Generative AI
emoji: 🌍
colorFrom: green
colorTo: red
sdk: streamlit
sdk_version: 1.38.0
app_file: app.py
pinned: false
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
# Legal Document Analysis on Hugging Face Spaces
This app allows lawyers to quickly analyze legal documents using AI models from Hugging Face. Upload a document, and the app will generate a summary or other relevant analysis.
## How to Use
- Upload a document (in .txt format).
- View the summary or analysis generated by the AI model.
Technologies:
streamlit
transformers
# to classify text as law-related or not using zero-shot classification
model="facebook/bart-large-mnli"
# "summarization"
model="facebook/bart-large-cnn"
#Named Entity Recognition (NER)
model="dslim/bert-base-NER"
Named Entity Recognition (NER) is a Natural Language Processing (NLP) technique used to identify and classify key information (entities)
in text. In the context of your legal document analysis project, NER plays an important role in extracting relevant entities such as names
of people, organizations, locations, dates, and more, which are crucial in legal texts.
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