Claude MarketplacesSubmit

Pyre Code Ml Practice

aradotso/trending-skills

If you want to actually understand how modern ML systems work under the hood, this gives you 68 coding problems that make you implement the internals yourself. You'll build pieces of Transformers, diffusion models, RLHF algorithms, and inference optimizations like Flash Attention and KV caching. It runs entirely in your browser with a local FastAPI grading service, no GPU needed. The setup is straightforward (one shell script or Docker Compose), and you get instant pass/fail feedback on each submission. It's self-hosted, so you can add your own problems or modify the test cases. Honestly, this is what LeetCode would look like if it cared about ML engineering instead of inverting binary trees.

skills.sh installs: 414
GitHub stars: 25
last updated: Jun 3, 2026

Install

$ npx -y skills add aradotso/trending-skills --skill pyre-code-ml-practice --agent claude-code

Installs into .claude/skills of the current project.

Files

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)

git clone https://github.com/whwangovo/pyre-code.git
cd pyre-code
./setup.sh
npm run dev

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

git clone https://github.com/whwangovo/pyre-code.git
cd pyre-code
conda create -n pyre python=3.11 -y && conda activate pyre
pip install -e ".[dev]"
npm install
npm run dev

Option C — Docker

git clone https://github.com/whwangovo/pyre-code.git
cd pyre-code
docker compose up --build

Progress persists in a Docker volume. Reset with docker compose down -v.

After installation

Grading service: http://localhost:8000
Web app: http://localhost:3000

SKILL.md on GitHub

Sponsors

Promote your product hereReach 125k+ visitors monthly Promote your product hereReach 125k+ visitors monthly

Agent CaffeineSponsoredClose your lid, come back to finished work

SnugSponsoredThe clipboard manager for the AI era Promote your product hereReach 125k+ visitors monthly

WaxSponsoredBlock anything with supervision, without erasing your iPhone Promote your product hereReach 125k+ visitors monthly

knobsSponsoredSee your site on any phone, any day, in any language

Details

Repository: github.com/aradotso/trending-skills
Category: Data Science & ML
First seen: Jun 3, 2026

Recommended

More Data Science & ML

1

tooluniverse-target-researchmims-harvard/tooluniverseComprehensive drug-target intelligence — tissue expression (GTEx, HPA), pathways, protein interactions (STRING), variant landscape (ClinVar, gnomAD), druggabili412skills.sh installs

2

content-research-writermoizibnyousaf/ai-agent-skillsAssists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on ea412skills.sh installs

3

user-research-synthesisanthropics/knowledge-work-pluginsSynthesize qualitative and quantitative user research into structured insights and opportunity areas. Use when analyzing interview notes, survey responses, supp409skills.sh installs

4

research-engineersickn33/antigravity-awesome-skillsresearch engineer409skills.sh installs

5

ml-pipeline-automationsecondsky/claude-skillsAutomate ML workflows with Airflow, Kubeflow, MLflow. Use for reproducible pipelines, retraining schedules, MLOps, or encountering task failures, dependency err402skills.sh installs

6

hypothesis-generationdavila7/claude-code-templatesGenerate testable hypotheses. Formulate from observations, design experiments, explore competing explanations, develop predictions, propose mechanisms, for scie396skills.sh installs