Agent skill · writing content · aradotso
pyre-code-ml-practice
Self-hosted ML coding practice platform with 68 problems covering Transformers, diffusion, RLHF, and more — instant browser feedback, no GPU required.
Why this skill is useful
Provides a structured environment for practicing ML coding with specific problem sets and instant feedback, which the AI wouldn't generate on its own.
What it needs
Requires docker, git, npm, python installed locally. Requires openai account access. About 7k tokens when loaded. Last updated 2026-07-09. 70 stars on the source repository.
What this skill does
Pyre Code ML Practice Platform Skill by ara.so — Daily 2026 Skills collection. Pyre Code is a self-hosted ML coding practice platform with 68 problems ranging from ReLU to flow matching. Users implement internals of modern AI systems (Transformers, vLLM, TRL, diffusion models) in a browser editor with instant pass/fail feedback, no GPU required. --- Installation Option A — One-liner (recommended) setup.sh creates a .venv (prefers uv, falls back to python3 -m venv), installs all Python deps, then prints the start command. Option B — Conda Option C — Docker Progress persists in a Docker volume. Reset with docker compose down -v. After installation Grading service: http://localhost:8000 Web app: http://localhost:3000 --- Project Structure --- Key Commands --- Configuration Environment Variables Create web/.env.local to override defaults: AI Help (Optional) Copy web/.env.example to web/.env and configure: Any OpenAI-compatible endpoint works: OpenAI, Anthropic via proxy, Ollama, etc. Users can also set their own key in the UI if no server-side config is present. --- Problem Categories Category Examples --- --- Fundamentals ReLU, Softmax, GELU, SwiGLU, Dropout, Embedding, Linear, Kaiming Init Normalization LayerNorm, BatchNorm, RMSNorm Attention Scaled Dot-Product, Multi-Head, Causal, GQA, Flash, Differential, MLA Position Encoding Sinusoidal PE, RoPE, ALiBi, NTK-aware RoPE Architecture GPT-2 Block, ViT Block, Conv2D, MoE, Depthwise Conv Training Adam, Cosine LR, Gradient Clipping, Mixed Precision, Activation Checkpointing Distributed Tensor Parallel, FSDP, Ring Attention Inference KV Cache, Top-k Sampling, Beam Search, Speculative Decoding, Paged Attention Alignment DPO, GRPO, PPO, Reward Model Diffusion Noise Schedule, DDIM Step, Flow Matching, adaLN-Zero Adaptation LoRA, QLoRA Reasoning MCTS, Multi-Token Prediction SSM Mamba SSM --- Adding a New Problem Problems live in torchjudge/problems/. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aradotso/pyre-code-ml-practice