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remote-reward-models

remote-reward-models

Operate Align-Anything remote reward servers, payload checks, and PPO remote-RM wiring.

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Documentación de la Skill

GitHub

name: remote-reward-models description: "Operate Align-Anything remote reward servers, payload checks, and PPO remote-RM wiring." metadata: disco-role: operating disable-model-invocation: true license: Apache 2.0

Remote Reward Models

Use this sub-skill when you need to:

  • start a local remote reward server
  • validate the HTTP payload contract
  • wire PPO training to a remote reward endpoint
  • debug address, port, dataset, reward-type, or reward-function failures

Fast route

  1. Read references/remote-rm-contract.md.
  2. Start the server with scripts/start_remote_rm_template.sh or the python -m align_anything.models.remote_rm.run_reward_server pattern.
  3. Validate /get_reward with scripts/probe_remote_rm_payload.py.
  4. If PPO still fails, check references/troubleshooting.md.
  5. For PPO remote RM, use the adapted qwen2_5_vl launch pattern captured here: start the reward server first, export REMOTE_RM_URL, then run deepspeed --module align_anything.trainers.text_to_text.ppo_remote_rm.

What this sub-skill covers

  • Flask reward server lifecycle
  • reward function registration and dataset-backed math verification
  • RemoteRewardModel client calls and retries
  • PPO remote RM config keys and launch order
  • common failures around payload shape, reward type, dataset mapping, and tokenizer mismatch

Primary facts

  • Server entry point: python -m align_anything.models.remote_rm.run_reward_server
  • HTTP endpoint: POST /get_reward
  • Client class: align_anything.models.remote_rm.remote_rm_client.RemoteRewardModel
  • PPO trainer: align_anything.trainers.text_to_text.ppo_remote_rm
  • Math verifier reward: math_verifier_reward_function
  • Bundled launch helpers: scripts/start_remote_rm_template.sh, scripts/probe_remote_rm_payload.py

What is out of scope

  • editing source implementation outside the skill tree
  • production hardening, auth, or multi-tenant deployment
  • non-HTTP reward training paths that do not use the remote RM server
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