openrlhf-training
De la autor
High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.
Instalare
npx skills add KalarisLabs/research-agent-skills --skill openrlhf-training -a claude-code
Se instalează în .claude/skills/openrlhf-training/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
Vrei ca agentul să-ți propună skill-uri în timp ce scrii? Vezi cum folosești skill-urile din IDE.
Verificări de siguranță pe SKILL.md
- Folosește sudoScăzut
De ce 80
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- verl-rl-trainingKalarisLabs/research-agent-skillsProvides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.DevOps★ 71
- fine-tuning-with-trlKalarisLabs/research-agent-skillsFine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.Altele★ 71
- axolotlOrchestra-Research/AI-Research-SKILLsExpert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal supportAltele★ 14K
- unslothericrisco/rsc-harnessUse when fine-tuning an open-weight LLM fast on ONE GPU with low VRAM — Unsloth's fast model loaders with 4-bit QLoRA and the trl trainer, response-only loss masking so the prompt is not trained on, GRPO reasoning fine-tunes, and export to merged 16-bit, GGUF or the Hub. NOT whether, why or which method to fine-tune (that is `finetuning`), NOT running the exported GGUF locally (that is `ollama`), NOT serving-engine flags and throughput (that is `vllm`), NOT building the JSONL dataset (that is `training-data`).Altele★ 350
- deepspeedOrchestra-Research/AI-Research-SKILLsExpert guidance for distributed training with DeepSpeed - ZeRO optimization stages, pipeline parallelism, FP16/BF16/FP8, 1-bit Adam, sparse attentionAltele★ 14K
- trl-traininghuggingface/skillsPost-train LLMs with TRL (Transformers Reinforcement Learning) — SFT, DPO, GRPO, KTO, and reward-model training. Use when writing or debugging training code with the TRL Python API or the trl CLI.OficialRedactare★ 11.2K
Note și recenzii
—
nicio recenzie
Ai încercat acest skill? Notează-l ca să-i ajuți pe alții. Autentifică-te
Discuție
Intră în discuție. Autentifică-te