AI/ML / Visualization
An interactive visualizer showing how a tiny byte-level language model learns 2D token embeddings during training. It includes controls for stepping, pausing, resetting, and adjusting training behavior while plotting the learned vectors.
The page clearly presents an interactive AI/ML demo with visible model architecture, training controls, and a live embedding plot. The snapshot shows enough concrete detail to understand the project, its purpose, and how a visitor would use it.
The snapshot does not show source code, installation instructions, or a broader explanation of the project beyond the demo itself. It also does not indicate whether the visualizer is part of a larger toolkit or what other examples are available.
Last evaluated 18 days ago. Current rank #1796. Holding steady in the rankings.
A detailed vLLM blog post explaining speculative decoding on AMD GPUs, with mechanics, supported drafting methods, configuration guidance, tuning advice, and benchmark discussion.
A technical blog post showing a tiny diffusion transformer running on an RP2350 microcontroller to generate 128×128 face images, with details on model design, quantization, and on-device inference.
An open-source project for making AI research agents legible, auditable, and traceable through behavioral code and event logs.
Market-derived RL environments for training agents on quant trading and long-horizon planning under adversarial noise.
