Stars
quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.
slee-lab / llama-recipes
Forked from meta-llama/llama-cookbookExamples and recipes for Llama 2 model
Code and data for the publication "Structured information extraction from scientific text with large language models" by Dagdelen & Dunn et al.
Colloid icon theme for linux desktops
🎵 A simple, clean and cross-platform music player
Generative materials benchmarking metrics, inspired by guacamol and CDVAE.
LaTeX.css is a CSS library that makes your website look like a LaTeX document
🔍 A Hex Editor for Reverse Engineers, Programmers and people who value their retinas when working at 3 AM.
Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.
RegEx-based text parser that converts chemical terms and material entities into chemical datastructure.
A tool for downloading songs from music streaming services like Spotify and Apple Music.
Files is a single-file PHP application that can be dropped into any directory, allowing browsing of files and directories inside.
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
Tutorials, notebooks, issue tracker, and website on the MPDS API: the data retrieval interface for the Materials Platform for Data Science
Utility to compile string of chemical terms into data structure with chemical formula and composition
ChemDataExtractor Version 2.0
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
The user-friendly command line shell.
A long term calorie/weight loss tracking iOS application designed to help individuals stay on track with their health and fitness goals.
Mirror of https://gitlab.redox-os.org/redox-os/redox
MatDeepLearn, package for graph neural networks in materials chemistry