wsheffel

wsheffel's Stars

• nomic-ai/gpt4all

  GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.

  Language:C++69.6k6401.9k7.6k

• microsoft/autogen

  A programming framework for agentic AI 🤖

  Language:Jupyter Notebook31.3k3801.6k4.6k

• varunshenoy/GraphGPT

  Extrapolating knowledge graphs from unstructured text using GPT-3 🕵️‍♂️

  Language:JavaScript4.3k5428387

• bytewax/bytewax

  Python Stream Processing

  Language:Python1.5k169358

• tomasonjo/blogs

  Jupyter notebooks that support my graph data science blog posts at https://bratanic-tomaz.medium.com/

  Language:Jupyter Notebook1.3k3940334

• tomhartke/knowledge-graph-from-GPT

  Using GPT to organize and access information, and generate questions. Long term goal is to make an agent-like research assistant.

  Language:Jupyter Notebook63915052

• luisguiserrano/manning

  Repository for the book Grokking Machine Learning, by Manning Editors

  Language:Jupyter Notebook4901410246

• acbull/GPT-GNN

  Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"

  Language:Python480124987

• tomasonjo/NeoGPT-Explorer

  Knowledge-graph based chatbot using GPT3 and Neo4j

  Language:Jupyter Notebook1839558

• dcavar/python-tutorial-notebooks

  Python tutorials as Jupyter Notebooks for NLP, ML, AI

  Language:Jupyter Notebook11912083

• Elyah2035/llama-dl

  Language:Shell821012

• kenshiro-o/nagato-ai

  Simple cross-LLM AI Agent library

  Language:Python81705

• liuzl/fmr

  Functional Meaning Representation and Semantic Parsing Framework

  Language:Go7842415

• chanind/frame-semantic-transformer

  Frame Semantic Parser based on T5 and FrameNet

  Language:Python5151610

• MixedEmotions/knowledge-graph

  Creates knowledge graph from information processed by "Entity Extraction and Linking" module, and "Emotion Recognition from Text" module

  Language:Python376111

• swabhs/coling18tutorial

  COLING 2018 Tutorial on Multilingual FrameNet: Automatic semantic role labeling for FrameNet

  Language:TeX25907

• ksm26/Multi-AI-Agent-Systems-with-crewAI

  Master the art of designing and organizing AI agents. Learn to automate complex, multi-step business processes by creating specialized AI agent teams using the open-source library crewAI.

  Language:Jupyter Notebook24209

• ronanmmurphy/Knowledge-Graph-Embeddings-to-Implement-Explainability

  Knowledge Graph Embeddings (KGE) to implement Explainable Artificial Intelligence. As AI develops users must know how algorithms make their decisions, especially for hazardous tasks such as driverless cars. Knowledge graphs are an inherently understandable form of text-based data created as an interconnected network of information. These can be converted into KGE by transforming the unqiue entites in the graph to vector representations. With these, predictions were made for missing/incorrect links in the network and further explainations were made by plotting the clusters of the data. Knowledge graphs and their embedded models were researched and four of these KGE were created and tested by their ability to rank the correct links from a Covid-19 dataset. This dataset was extracted from research papers about the virus to retrieve information quicker. The model which was most accurate was used to implement knowledge graph completion and explainability of the dataset using visual and textual interpretations. A 29,000-word thesis was written to describe the work done through the researching, testing and interpreting of this project.

  Language:Jupyter Notebook121

• UKPLab/framenet-tools

  Annotate text with FrameNet frames and arguments.

  Language:Jupyter Notebook103142

• AlexanderProchnow/scitext

  An automatic Text-to-Knowledge-Graph pipeline that was built to create knowledge graphs from scientific papers and evaluate them automatically.

  Language:Python9102

• FrameNetBrasil/webtool

  FrameNet Brasil Web Annotation Tool

  Language:JavaScript76116

• m477301/KnowledgeGraphVerbalizer

  These last years have witnessed the rise of knowledge graph technologies. Practically, semi-structured datasets (often available online through APIs and endpoints) allow data practitioners to build up complex use-cases interconnecting multiple data sources. However, technologies are often operating as black boxes and the need for explainability is increasing, in particular to keep track of the intermediate steps of the data pipelines. In this project, we would like the group to explore the possibility of verbalizing (creating a narrative) from knowledge graph excerpts. Technically, a browser interface able to query an open knowledge graph and render a text using for instance SimpleNLG <https://github.com/simplenlg/simplenlg> is envisioned.

  Language:JavaScript63191

• ambareeshravi/Knowledge_Graphs-Text

  Creating knowledge graphs from entities in large chunks of text

  Language:Python2100

• camilouribebotta/visual-essays

  Tools for creating interactive essays from text, knowledge graphs, and other web content

  Language:Python2001

• zaneprice5/knowledge-graph-with-spaCy

  Creating a basic knowledge graph with spaCy and text data from the New York Times

  Language:Jupyter Notebook2100

• KarthickMayorBat/Knowledge-graph-creation

  This project is used to create knowledge graphs from the given input text and it would be used in analysing nlp parts

  Language:Jupyter Notebook1

• makrandbhonde/Triplet-extraction-from-text-and-creating-graph

  Grammar Based triplet extraction from text & knowledge graph creation with visualization. Building a flask-based web application to create a knowledge graph with unstructured data.

  Language:Python110

• project-renard-survey/visual-essays

  Tools for creating interactive essays from text, knowledge graphs, and other web content

  Language:Python1100

• sandeepnair2812/JohnSnowLabs-spark-nlp-workshop

  Language:Jupyter Notebook1001

• SushantTha7/Knowledge_graph_from_Text_scraped_article

  An application that scrape news article and creates a knowledge graph from it

  Language:Jupyter Notebook1100