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Evidera RWDS
- Miami, Florida
- https://www.linkedin.com/in/jjborie
Starred repositories
Multi-agent that helps you organize and write documents.
AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation
Teaching materials for the applied machine learning course at Cornell Tech (online edition)
Examples and guides for using the Gemini API
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
An overview of LLMs for cybersecurity.
A benchmark for cyber security knowledge evaluation on LLM
Container Management and Kubernetes on the Desktop
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Benchmarks of approximate nearest neighbor libraries in Python
A library for efficient similarity search and clustering of dense vectors.
Links to conference/journal publications in automated fact-checking (resources for the TACL22/EMNLP23 paper).
Build large language model (LLM) apps with Python, ChatGPT and other models. This is the companion repository for the book on generative AI with LangChain.
The missing star history graph of GitHub repos - https://star-history.com
Drag & drop UI to build your customized LLM flow
LLM based autonomous agent that conducts local and web research on any topic and generates a comprehensive report with citations.
Large Language Models: In this repository Language models are introduced covering both theoretical and practical aspects.
Calculate perplexity on a text with pre-trained language models. Support MLM (eg. DeBERTa), recurrent LM (eg. GPT3), and encoder-decoder LM (eg. Flan-T5).
A simple Python program to implement the search-extract-summarize flow.
Detect AI-generated text [relatively] quickly via compression ratios
Continuously updated list of related resources for generative LLMs like GPT and their analysis and detection.
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
the AI-native open-source embedding database