Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.
Toolkit for Machine Learning, Natural Language Processing, and Text Generation, in TensorFlow. This is part of the CASL project: http://casl-project.ai/
A 4th-sem AI Lab research project providing a comparative study of six Transformer popular models evaluated on accuracy and computational efficiency using Emotion Detection dataset.
Annotations of the interesting ML papers I read
Ontology-driven knowledge graph system for biomedical NER and relation extraction across diagnosis, prognosis & treatment in neurodegenerative diseases.
Fine-tuned XLNet for multi-label intent + VADER sentiment on Google Play Store reviews (Streamlit)
Streamlit web app: scrapes Google Play Store reviews, runs VADER sentiment + fine-tuned XLNet multi-intent classification
Pre-Trained Chinese XLNet（中文XLNet预训练模型）
🛸 Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
AI-powered legal NLP system for Indian court cases: case summarization, judgement outcome prediction (Accepted/Rejected), explainability, and a RAG-based legal chatbot.
Identify fake news and real news using algorithms like bert,Roberta,Xlnet,Explainable AI with Shap and Nlp techniques on tested data.
The "LLM Projects Archive" is a centralized GitHub repository, offering a diverse collection of Language Model Models projects. A valuable resource for researchers, developers, and enthusiasts, it showcases the latest advancements and applications in the realm of LLMs. Explore and contribute to the dynamic landscape of language model projects.
Transformer Architectures for Generative AI
Deep learning models for sentiment analysis on disaster tweets
This repository focuses on detecting suicidal ideation on Twitter using NLP and ML models, including Logistic Regression, SVM, RF, MNB, Ensemble Learning, AdaBoost, LSTM, GRU, CNN, and BERT. This project aims to identify individuals who may be at risk of suicide and contribute to suicide prevention efforts.
A cutting-edge, modular framework for classifying tweets into mental health categories using advanced Natural Language Processing (NLP) and Machine Learning (ML) techniques.
Affevtive Bias in Large Pre-trained Language Models
This project explores whether Mathematics and Computer Science texts still retain enough linguistic patterns (metalanguage) for classification once domain-specific words are removed. 🤖📚
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