You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
- Out-of-the-box implementations of popular RL algorithms, including [PPO](https://github.com/modelscope/Trinity-RFT/tree/main/examples/ppo_countdown), [GRPO](https://github.com/modelscope/Trinity-RFT/tree/main/examples/grpo_gsm8k), [GSPO](https://github.com/modelscope/Trinity-RFT/tree/main/examples/gspo_gsm8k), [TOPR](https://github.com/modelscope/Trinity-RFT/tree/main/examples/topr_gsm8k), [REC](https://github.com/modelscope/Trinity-RFT/tree/main/examples/rec_gsm8k), [sPPO](https://github.com/modelscope/Trinity-RFT/tree/main/examples/sppo_gsm8k), and more.
89
-
- Easily extendable to new algorithms by flexibly composing modular components such as policy loss (e.g., [CISPO](https://github.com/modelscope/Trinity-RFT/tree/main/trinity/algorithm/policy_loss_fn/cispo_policy_loss.py), [SAPO](https://github.com/modelscope/Trinity-RFT/tree/main/trinity/algorithm/policy_loss_fn/sapo_policy_loss.py)), advantage estimation (e.g., [RLOO](https://github.com/modelscope/Trinity-RFT/tree/main/trinity/algorithm/advantage_fn/rloo_advantage.py), [REINFORCE](https://github.com/modelscope/Trinity-RFT/tree/main/trinity/algorithm/advantage_fn/reinforce_advantage.py)), and more.
90
-
- Hybrid approaches like [CHORD](https://github.com/modelscope/Trinity-RFT/tree/main/examples/mix_chord) (SFT+RL integration) and [LLM-as-a-judge](https://github.com/modelscope/Trinity-RFT/tree/main/examples/grpo_rubric_as_reward) reward modeling.
88
+
89
+
| Algorithm [Paper]| Documentation | Key Configurations | Example |
0 commit comments