peft-fine-tuning SKILL.md skillA
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peft-fine-tuning from yichen-zju/claude-for-research is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add yichen-zju/claude-for-research/peft-fine-tuning@v1.0.0Pins v1.0.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- yichen-zju/claude-for-research
- Path
claude/skills/peft/SKILL.md- Versions recorded
- 1
- Latest version
- v1.0.0, committed Oct 14, 2026
- Size
- 12,210 bytes
- Repository stars
- 10
- License
- none declared
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# 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) ```python from transformers import AutoModelForCausalLM, AutoTokenizer, TrainingArguments, Trainer …
Read the whole file at its exact version.
How to install
mdr add yichen-zju/claude-for-research/peft-fine-tuning@sha256:acdb318f94624517The line at the top of this page pins the label v1.0.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_zf3vxff73sqaqg2g)
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Versions
The registry has recorded 1 version of this file, committed on Oct 14, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (12210 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
yichen-zju/claude-for-research · 10 stars · license none declared · pushed 2026-10-21 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_zf3vxff73sqaqg2g GET https://markdownregistry.com/api/v1/resolve?ref=yichen-zju/claude-for-research/peft-fine-tuning GET https://markdownregistry.com/api/v1/blob/acdb318f94624517c8cdb3c925c7a2e8b34c65e8ca02b301777c51eea9f0f73c
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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