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walkinglabs/hands-on-modern-rl

🚀 An open-source, hands-on curriculum bridging the gap from basic RL concepts to LLM alignment, RLVR, and advanced Agentic systems.

Latest metrics (snapshot 2026-10-14)

stars4643
forks335
issues19
pushed_at2026-10-01T11:39:50Z

History

History chart: 1 daily snapshot so far (archive started 2026-10-14). The line fills in as the daily archive grows; full series via the API.

DateGitHub stars
2026-10-144643

ADC Momentum: 49/100

ADC Momentum 49 Leaderboard

Growth velocity63
Consistency50
Recency52
Agent demand0
Basisbootstrap

ADC Momentum (0-100) = 45% growth velocity (stars/likes gained per day in our daily archive, relative and absolute, percentile-ranked within the category) + 20% consistency (share of recent days with growth) + 20% recency (latest push/update/release, decaying) + 15% agent demand (how often AI agents looked it up via our API/MCP this week). MCP servers use release cadence; LLMs use price cuts, context and recency. Recomputed daily; scores marked "bootstrap" use lifetime rates until the archive has enough days. Method

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Details

description🚀 An open-source, hands-on curriculum bridging the gap from basic RL concepts to LLM alignment, RLVR, and advanced Agentic systems.
urlhttps://github.com/walkinglabs/hands-on-modern-rl
languagePython
licenseNOASSERTION
topicsagent
agentic
agentic-ai
agentic-rl
dpo
grpo
llm
llm-alignment
ppo
pytorch
reinforcement
reinforcement-learning
created_at2026-04-10T01:25:58Z
homepagehttps://walkinglabs.github.io/hands-on-modern-rl/

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