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🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Machine Learning Engineering Open Book
Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.
Easy-to-use and powerful LLM and SLM library with awesome model zoo.
A PyTorch-based Speech Toolkit
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Open-source offline translation library written in Python
Seamlessly integrate LLMs into scikit-learn.
Multilingual Automatic Speech Recognition with word-level timestamps and confidence
Turn any LLM into a Jev-style decision model: typed decisions, real probabilities, no training. (continue updating, welcome any issue and PR request)
A computer, compiled into the weights of a language model. An exact CPU inside Qwen3.5-4B, with Gated DeltaNet state as RAM.
Python package implementing ML feature engineering and pre-processing for polars or pandas dataframes.
Universal 1d/2d data containers with Transformers functionality for data analysis.
Code and data for the paper "Evaluating German Transformer Language Models with Syntactic Agreement Tests" (Zaczynska et al., 2020)