{"enrichment":{"faq":[{"a":"fine-tuning-with-trl covers Direct Preference Optimization (DPO) as a key method for aligning language models with human preferences. DPO trains models directly on preference pairs without requiring a separate reward model, making it more efficient than traditional RLHF. The skill includes practical examples and implementation guidance for applying DPO to your models.","q":"What does fine-tuning-with-trl teach about DPO for LLM alignment?"},{"a":"fine-tuning-with-trl teaches the full RLHF workflow: starting with supervised fine-tuning (SFT) on instruction data, then training a reward model to score outputs based on preference data, and finally running online RL using methods like RLOO or GRPO. The skill provides step-by-step guidance and code examples for each stage.","q":"How do I implement a complete RLHF pipeline using fine-tuning-with-trl?"},{"a":"Yes. fine-tuning-with-trl covers reward model training to score language model outputs based on human preference data. This is a critical component of preference alignment pipelines. The skill explains how to prepare preference datasets and train models that effectively distinguish between better and worse outputs.","q":"Can fine-tuning-with-trl help me train a reward model?"},{"a":"fine-tuning-with-trl covers SFT (supervised fine-tuning), DPO (direct preference optimization), RLOO (online reinforcement learning), and GRPO (group relative policy optimization). The skill helps you choose between these methods based on your use case, considering factors like computational efficiency, data requirements, and alignment quality.","q":"What alignment methods does fine-tuning-with-trl compare?"},{"a":"fine-tuning-with-trl includes troubleshooting guidance for common preference alignment challenges like out-of-memory errors, poor output quality, and training instability. The skill provides practical solutions and best practices to help you debug and optimize your alignment training workflows.","q":"How does fine-tuning-with-trl address training instability and memory issues?"},{"a":"fine-tuning-with-trl is released under the MIT license, allowing free use, modification, and distribution for both commercial and personal projects.","q":"What is the license for fine-tuning-with-trl?"}],"shadow_tags":["instruction-tuning","policy-optimization","human-feedback-learning","model-alignment","reward-scoring","online-reinforcement-learning","preference-data","llm-training-pipeline","memory-efficient-training","loss-function-variants"],"summary_rewrite":"This skill teaches post-training techniques for aligning language models to human preferences. It covers supervised fine-tuning, direct preference optimization (DPO), and online reinforcement learning methods like RLOO and GRPO, with complete workflows and practical examples."},"files":[{"bytes":13510,"path":"optional-skills/mlops/training/trl-fine-tuning/SKILL.md","sha256":"5b00e9b9782bd2d5f870d96cb5a8aa8b1e3609a40bf909915d32ed8bad064898","url":"https://skillfed.io/files/NousResearch/hermes-agent/trl-fine-tuning/e1f1cd0d/SKILL.md"}],"id":"NousResearch/hermes-agent/trl-fine-tuning","links":{"html":"https://skillfed.io/NousResearch/hermes-agent/trl-fine-tuning","md":"https://skillfed.io/NousResearch/hermes-agent/trl-fine-tuning.md","repo":"https://github.com/NousResearch/hermes-agent"},"meta":{"agents_supported":[],"first_seen":"2026-07-28","forks":42317,"language":"Python","last_updated":"2026-07-28","license":"MIT","name":"fine-tuning-with-trl","publisher":"NousResearch","stars":221503},"relations":{"similar":[{"id":"synthetic-sciences/openscience/trl-fine-tuning"},{"id":"Orchestra-Research/AI-Research-SKILLs/trl-fine-tuning"},{"id":"OpenLAIR/dr-claw/trl-fine-tuning"},{"id":"moltis-org/moltis/fine-tuning-with-trl"},{"id":"graniet/kheish/trl-fine-tuning"},{"id":"huggingface/skills/trl-training"},{"id":"BagelHole/DevOps-Security-Agent-Skills/llm-fine-tuning"},{"id":"synthetic-sciences/openscience/hugging-face-model-trainer"},{"id":"huggingface/skills/huggingface-llm-trainer"},{"id":"synthetic-sciences/openscience/unsloth"}]},"slug":{"owner":"NousResearch","repo":"hermes-agent","skill":"trl-fine-tuning"},"version":"e1f1cd0d"}