Stars
Modeling, training, eval, and inference code for OLMo
You like pytorch? You like micrograd? You love tinygrad! ❤️
This repository shows how Svelte and SvelteKit work together with TypeScript.
Diffusers-Interpret 🤗🧨🕵️♀️: Model explainability for 🤗 Diffusers. Get explanations for your generated images.
Entropy based binning of discrete variables.
Solve puzzles. Improve your pytorch.
Pen and paper exercises in machine learning
Well documented, unit tested, type checked and formatted implementation of a vanilla transformer - for educational purposes.
Original transformer paper: Implementation of Vaswani, Ashish, et al. "Attention is all you need." Advances in neural information processing systems. 2017.
Papers & presentation materials from Hugging Face's internal science day
🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Repository containing notebooks of my posts on Medium
As described in Advances of Machine Learning by Marcos Prado.
Generate bootstrapped confidence intervals for A/B testing in Python.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
A Scala feature transformation library for data science and machine learning
Common library for serving TensorFlow, XGBoost and scikit-learn models in production.
Provides Spotify-specific TensorFlow helpers
A Scala API for Apache Beam and Google Cloud Dataflow.
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Probabilistic Modeling Toolkit for Matlab/Octave.
Javascript library for rapid A/B-testing with Sequential Generalized Likelihood Ratio tests