This repository provides a collection of diverse machine learning models implemented using the Flux library in Julia. It serves as a practical resource for developers and researchers to explore, learn from, and build upon various neural network architectures for tasks in computer vision, natural language processing, and reinforcement learning.

How It Works

The Model Zoo organizes implementations into folders like vision, text, and games, with each model contained within its own Julia project directory. This structure ensures reproducible environments by pinning package versions via Project.toml and Manifest.toml. Models are designed to be easily runnable and can leverage NVIDIA GPU acceleration through calls to gpu.

Quick Start & Requirements

• Install: Navigate to a model's directory and run julia -e 'using Pkg; Pkg.activate("."); Pkg.instantiate()'
• Run: include("<model-to-run>.jl")
• Prerequisites: Julia, optional NVIDIA GPU with CUDA.
• Online IDE: Gitpod integration is available, with usage subject to Gitpod's free tier policies.
• Documentation: FluxML website Tutorials

Highlighted Details

• Features models for MNIST, CIFAR10, NLP tasks (CharRNN, NanoGPT), and Reinforcement Learning.
• Demonstrates various Flux API features, including explicit gradients (v0.13+).
• Includes examples for generative models (GANs, Diffusion Models) and spatial transformers.
• Offers guidance on contributing new models and improving documentation.

Maintenance & Community

The project encourages contributions and provides guidelines for sharing new models and documentation. It lists Flux versions used for each example, aiding in updates.

Licensing & Compatibility

The repository's licensing is not explicitly stated in the README. Compatibility with commercial or closed-source projects would require clarification on the license terms.

Limitations & Caveats

Some older examples are marked with ⛅️ and use Flux v0.11, requiring Julia 1.6. Newer examples are marked with ☀️ and are compatible with Flux v0.13/v0.14. Models marked with ❄️ are significantly older (v0.6/v0.7) and may require substantial updates.