peft Skill
Fine-tune large LLMs with LoRA on limited GPU memory. Published by NousResearch in hermes-agent.
Decision snapshot
Is this a fit?
Developers using hermes-agent, Includes SKILL.md, Reusable instructions
Compatibility not yet detected.
Permission behavior not yet detected.
Copy skill directory
22 days ago · MIT license
No specific cautions were detected. Review the source and requested permissions before installing.
What is peft Skill?
Fine-tune large LLMs with LoRA on limited GPU memory. Published by NousResearch in hermes-agent. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Developers using hermes-agent
Declared skill metadata
- Declared author: Orchestra Research
- Declared license: MIT
- Source file: optional-skills/mlops/peft/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
When to use peft Skill
- Use it for developers using hermes-agent.
Built with
Editorial notes
Source
- Creator: NousResearch
- Repository: NousResearch/hermes-agent
- Skill file: optional-skills/mlops/peft/SKILL.md
What it does
Fine-tune large LLMs with LoRA on limited GPU memory.
Skill instructions
PEFT (Parameter-Efficient Fine-Tuning) Fine-tune LLMs by training <1% of parameters using LoRA, QLoRA, and 25+ adapter methods. When to use PEFT Use PEFT/LoRA when: - Fine-tuning 7B-70B models on consumer GPUs (RTX 4090, A100) - Need to train <1% parameters (6MB adapters vs 14GB full model) - Want fast iteration with multiple task-specific adapters - Deploying multiple fine-tuned variants from one base model Use QLoRA (PEFT + quantization) when: - Fine-tuning 70B models on single 24GB GPU - Memory is the primary constraint - Can accept ~5% quality trade-off vs full fine-tuning Use full fine-tuning instead when: - Training small models (<1B parameters) - Need maximum quality and have compute budget - Significant domain shift requires updating all weights Quick start Installation bash Basic installation pip install peft With quantization support (recommended) pip install peft bitsandbytes Full stack pip install peft transformers accelerate bitsandbytes datasets LoRA fine-tuning (standard
Verified compatibility and discovery
Frequently asked questions
What is peft?
peft is a open-source AI agent skill with Copy skill directory. Fine-tune large LLMs with LoRA on limited GPU memory.
Who is peft best for?
peft is best for reusing agent instructions, scripts, and references.
How do I install peft?
Install or run peft using Copy skill directory. Check peft for the latest setup command.
Is peft actively maintained?
peft may need a closer maintenance check before production use.
Project health auto-fetched from the source repository.
Maintain this resource?
Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.
