Search Results for "json visualization"

Archify is an agent skill and rendering system for turning codebases or system descriptions into polished technical diagrams. It works with coding agents such as Claude Code, Codex CLI, Cursor, and OpenCode. Agents generate typed JSON representations that Archify deterministically compiles into self-contained HTML and SVG. It supports architecture, workflow, sequence, data-flow, and lifecycle diagrams. Interactive viewers provide search, route tracing, upstream and downstream exploration,...

ARC-AGI-1 Task Generator creates new ARC-style reasoning tasks whose distribution is designed to resemble the public ARC-AGI-1 evaluation set. It provides fresh problems that models are less likely to have encountered during training or previous evaluation. The project is intended to complement public benchmark scores by testing whether reasoning abilities transfer to newly generated examples. Generated tasks use the standard ARC train-and-test JSON structure. This makes the output...

profile-data is a repository that publishes profiling traces and metrics from DeepSeek’s training and inference infrastructure (especially during DeepSeek-V3 / R1 experiments). The profiling data targets insights into computation-communication overlap, pipeline scheduling (e.g. DualPipe), and how MoE / EP / parallelism strategies interact in real systems. The repository contains JSON trace files like train.json, prefill.json, decode.json, and associated assets. Users can load them into tools...

python-small-examples is an open-source educational repository that contains hundreds of concise Python programming examples designed to illustrate practical coding techniques. The project focuses on teaching programming concepts through small, focused scripts that demonstrate common tasks in data processing, visualization, and general programming. Each example highlights a specific function or programming pattern so that learners can quickly understand how to apply Python features in real-world scenarios. The repository includes examples covering topics such as file processing, JSON manipulation, data visualization, and library usage. The examples are intentionally short and easy to read, making them useful for beginners who want to understand Python syntax and programming logic step by step. ...

MLP Network Configurator is an interactive educational tool designed to help users understand how artificial neural networks work. It provides real-time training feedback, intuitive architecture visualization, and even camera-based dataset collection — ideal for students, teachers, hobbyists, and curious minds. 💡 Key Features - Data Handling: Load, normalize, and validate datasets (JSON format). - Model Configuration: Define hidden layers, activation functions, loss and optimizer types. - Training: Visualize loss curves, predictions, PCA-based class separation...