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Scripts, algorithms and files for a rule-based and ML-based approach for binary classification of regulatory / non-regulatory sentences in EU legislative documents, as well as code for evaluating the accuracy of these approaches
Implemented projects from noncontextual word embeddings like Word2Vec to contextual word embeddings like ELMO, GPT, BERT to solving NLP tasks Sentence Level Classification (sentimental analysis & Toxic comment classification), Token Level Classification (POS Tagging, NER Tagging), Machine Translation (MT)
Trained models & code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using ⚡ Pytorch Lightning and 🤗 Transformers. For access to our API, please email us at contact@unitary.ai.
This repository houses the source code for a Streamlit-based annotation interface developed for classifying sentences in legal documents. The interface is a part of a broader initiative to analyze court statements, specifically focusing on assessing judicial attitudes toward victims of sexual violence in the Israeli court system.