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Minimal and clean examples of machine learning algorithms implementations
DSPy: The framework for programming—not prompting—foundation models
LinearBoost Classifier is a rapid and accurate classification algorithm that builds upon a very fast, linear classifier.
Distribute and run LLMs with a single file.
llama3 implementation one matrix multiplication at a time
Solve puzzles. Improve your pytorch.
Implementation of Alpha Fold 3 from the paper: "Accurate structure prediction of biomolecular interactions with AlphaFold3" in PyTorch
An efficient, flexible and full-featured toolkit for fine-tuning LLM (InternLM2, Llama3, Phi3, Qwen, Mistral, ...)
Machine Learning Engineering Open Book
A playbook for systematically maximizing the performance of deep learning models.
A JAX research toolkit for building, editing, and visualizing neural networks.
The nnsight package enables interpreting and manipulating the internals of deep learned models.
A reactive notebook for Python — run reproducible experiments, execute as a script, deploy as an app, and version with git.
Opinionated cookiecutter template for creating a new Python library
Calculates various features from time series data. Python implementation of the R package tsfeatures.
Lightning ⚡️ fast forecasting with statistical and econometric models.
Python programs, usually short, of considerable difficulty, to perfect particular skills.