A collection of Jupyter notebooks and resources to guide you step-by-step through preparing data, building, and training your own Large Language Models (LLMs) step-by-step. Perfect for developers, …

Educational framework exploring ergonomic, lightweight multi-agent orchestration. Managed by OpenAI Solution team.

Implementing a ChatGPT-like LLM in PyTorch from scratch, step by step

The Clay Foundation Model (in development)

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

Foundation Architecture for (M)LLMs

12 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

🐢 The testing framework for ML models, from tabular to LLMs

Repo for "Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture"

MetisFL is a federated learning framework that allows developers to easily federate their machine learning workflows and train their models across distributed data silos without ever collecting the…

A collection of AWESOME things about mixture-of-experts

TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.

Web UI to run alpaca model locally

Generate 3D objects conditioned on text or images

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

PyTorch implementation of "data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language" from Meta AI

An interactive NVIDIA-GPU process viewer and beyond, the one-stop solution for GPU process management.

[Preprint] OneFormer: One Transformer to Rule Universal Image Segmentation, 2022

Set of Jupyter Notebooks linked to Roboflow Blogpost and used in our YouTube videos.