PRIME-RL/PRIME
Scalable RL solution for advanced reasoning of language models observed · 2026-08-28
Health v2 · maintenance only
26/100
- Activity 12
- Release rhythm 35
- Longevity 43
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 610
- days_rel: n/a
- days_push: 533
- n_releases_24m: 0
Adoption not part of the score
1871 stars · 116 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
PRIME (Process Reinforcement through Implicit Rewards) is an open-source Python framework for online reinforcement learning with process rewards to improve language model reasoning. It provides training, data preprocessing, and evaluation code, and has been integrated into the veRL framework.
Use cases
- train language models with reinforcement learning for math reasoning
- run online RL with process rewards on LLMs
- reproduce PRIME paper results on reasoning benchmarks
- preprocess math datasets for RL training
- train implicit process reward models
- improve LLM reasoning beyond distillation
When to choose
- you want to apply process-based RL to improve LLM reasoning
- you need an open-source, scalable RL training pipeline for language models
- you want to reproduce or build on the PRIME research results
When to avoid
- you only need inference or serving of LLMs without training
- you need a simple supervised fine-tuning pipeline without RL
- you lack multi-GPU infrastructure for large-scale training
Facets
library · maturity active
llm-training reinforcement-learning machine-learning large-language-models machine-learning artificial-intelligence python rlhf process-reward-model reasoning implicit-rewards verl gpu linux
1 source
- readme: https://github.com/PRIME-RL/PRIME · fetched 2026-08-28 · f56686a50f1b
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| PRIME-RL/PRIME | main | 26 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem