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A newer version of the Streamlit SDK is available: 1.41.1

Upgrade
metadata
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.