Examples Gallery

CodefyUI ships a library of ready-to-run example graphs under examples/. Load them from the Examples menu in the app, or run them headless with the CLI Graph Runner.

Category	Examples
Model Architecture	ResNet, ConvNeXt, EfficientNet, UNet, ViT, SwinTransformer, BERT, GPT, LLaMA, DiT, LSTM TimeSeries, BiGRU SpeechRecognition, Seq2Seq Attention, DQN Atari, PPO Robotics
Usage Example	CNN-MNIST Training, CNN-MNIST Inference, GPT-Mini Training, ResNet-CIFAR10 Training
LLM	Word Embedding Analogy (king − man + woman ≈ queen with the offline demo-16d backend)

The repository also groups examples by topic on disk: Classical/, Diffusion/, LLM/, Model_Architecture/, RL/, RNN/, Transformer/, Usage_Example/, and Others/.

Loading an example

• In the app — open the Examples menu and pick a graph; it loads into a new tab ready to Run.

• From the CLI — point run_graph.py at the graph's JSON:

  cd backend
  python run_graph.py ../examples/Usage_Example/CNN-MNIST/TrainCNN-MNIST/graph.json

A good first run

Load Train CNN on MNIST, then:

1. Turn on Record outputs and Persist weights between runs in the Settings popover.
2. Click Run and watch the live loss chart in the Training tab.
3. Click a Conv2d node to inspect its kernels and activations in the Teaching Inspector.
4. Run again — with weights persisted, the model keeps learning across runs.