Starred repositories
Archive of Windows samples from the legacy DirectX SDK
Neovim plugin to generate text using LLMs with customizable prompts
An open-source RAG-based tool for chatting with your documents.
🤖 A PyTorch library of curated Transformer models and their composable components
<⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.
As a believer of learning through examples, I have decided to put my own examples of Gremlin queries inside Jupyter Notebooks for people to actually try out. The course is roughly based on this boo…
A resource list for causality in statistics, data science and physics
Robust Speech Recognition via Large-Scale Weak Supervision
🔎 Open source distributed and RESTful search engine.
Custom recipe and utilities for document processing
NetworkX-based Python library for representing ontologies
🧙 Build, run, and manage data pipelines for integrating and transforming data.
Fuzzy string matching, grouping, and evaluation.
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
Zero-ETL, infinite possibilities. Live query APIs, code & more with SQL. No DB required.
The simplest way to serve AI/ML models in production
LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source …
The AI Datastore for Schemas, BLOBs, and Predictions. Use with your apps or integrate built-in Human Supervision, Data Workflow, and UI Catalog to get the most value out of your AI Data.
Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning
Research code implementing the search AI agent for Hanabi, as well as a web server so people can play against it
Community maintained fork of pdfminer - we fathom PDF
Google Research
DALL·E Mini - Generate images from a text prompt
A curated list of awesome posts, videos, and articles on leading a data team (small and large)
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
Operate and manipulate physical quantities in Python
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.