Peft Fine Tuning
Orchestra-Research/AI-Research-SKILLs
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods.
Plans fine-tuning runs (LoRA/QLoRA/full) with dataset curation, hyperparams, and eval — picks SFT vs DPO vs RLHF.
Install LLM Finetuning Strategist
$ npx skills add criptogus/agent-evolve-network --skill llm-finetuning-strategist -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install criptogus/agent-evolve-network llm-finetuning-strategist --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/criptogus/agent-evolve-network.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/llm-finetuning-strategist .claude/skills/llm-finetuning-strategist && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "llm-finetuning-strategist" agent skill from https://github.com/criptogus/agent-evolve-network/tree/main/skills/llm-finetuning-strategist into .claude/skills/llm-finetuning-strategist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-finetuning-strategist", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/criptogus/agent-evolve-network/tree/main/skills/llm-finetuning-strategistType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add criptogus/agent-evolve-network --skill llm-finetuning-strategist -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install criptogus/agent-evolve-network llm-finetuning-strategist --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/criptogus/agent-evolve-network.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/llm-finetuning-strategist .agents/skills/llm-finetuning-strategist && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "llm-finetuning-strategist" agent skill from https://github.com/criptogus/agent-evolve-network/tree/main/skills/llm-finetuning-strategist into .agents/skills/llm-finetuning-strategist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-finetuning-strategist", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add criptogus/agent-evolve-network --skill llm-finetuning-strategist -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install criptogus/agent-evolve-network llm-finetuning-strategist --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/criptogus/agent-evolve-network.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/llm-finetuning-strategist .cursor/skills/llm-finetuning-strategist && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "llm-finetuning-strategist" agent skill from https://github.com/criptogus/agent-evolve-network/tree/main/skills/llm-finetuning-strategist into .cursor/skills/llm-finetuning-strategist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-finetuning-strategist", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/criptogus/agent-evolve-network.git --path skills/llm-finetuning-strategist--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add criptogus/agent-evolve-network --skill llm-finetuning-strategist -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install criptogus/agent-evolve-network llm-finetuning-strategist --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/criptogus/agent-evolve-network.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/llm-finetuning-strategist .gemini/skills/llm-finetuning-strategist && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "llm-finetuning-strategist" agent skill from https://github.com/criptogus/agent-evolve-network/tree/main/skills/llm-finetuning-strategist into .gemini/skills/llm-finetuning-strategist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-finetuning-strategist", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install criptogus/agent-evolve-network llm-finetuning-strategistInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add criptogus/agent-evolve-network --skill llm-finetuning-strategist -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/criptogus/agent-evolve-network.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/llm-finetuning-strategist .github/skills/llm-finetuning-strategist && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "llm-finetuning-strategist" agent skill from https://github.com/criptogus/agent-evolve-network/tree/main/skills/llm-finetuning-strategist into .github/skills/llm-finetuning-strategist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-finetuning-strategist", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add criptogus/agent-evolve-network --skill llm-finetuning-strategist -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install criptogus/agent-evolve-network llm-finetuning-strategist --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/criptogus/agent-evolve-network.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/llm-finetuning-strategist .opencode/skills/llm-finetuning-strategist && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "llm-finetuning-strategist" agent skill from https://github.com/criptogus/agent-evolve-network/tree/main/skills/llm-finetuning-strategist into .opencode/skills/llm-finetuning-strategist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-finetuning-strategist", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
llm-finetuning-strategist- GitHub stars
- 288
- Token cost
- ~564 tokens
- SKILL.md length
- 165 words
- Files
- 1
- Skills in repo
- 107
- Repo updated
- First seen
- Licence
- CC-BY-SA-4.0
At a glance
Plans fine-tuning runs (LoRA/QLoRA/full) with dataset curation, hyperparams, and eval — picks SFT vs DPO vs RLHF.
- The user asks for llm fine-tuning strategist work
- SKILL.md covers Instructions, Always, Never and Examples, plus 1 more section
- Calls npx
- Tasks that involve Fine-tuning
What it does
LLM Finetuning Strategist is an agent skill from criptogus/agent-evolve-network. Plans fine-tuning runs (LoRA/QLoRA/full) with dataset curation, hyperparams, and eval — picks SFT vs DPO vs RLHF. Use when the user asks for llm fine-tuning strategist work, or mentions llm, finetuning, strategist.
Its SKILL.md is about 560 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering Fine-tuning. The licence is CC-BY-SA-4.0.
When your agent uses it
- The user asks for llm fine-tuning strategist work
- Tasks that involve Fine-tuning
Example prompts
- “Use the llm-finetuning-strategist skill to plan fine-tuning runs (LoRA/QLoRA/full) with dataset curation, hyperparams, and eval — picks SFT vs DPO…”
- “/llm-finetuning-strategist”
Requirements
- Node.js
What it can do on your machine
Read from SKILL.md and the folder at commit d19b920. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
npx
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
superagentskill.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
LLM Finetuning Strategist loads about 564 tokens when it runs. Until then it costs about 60 tokens; SKILL.md has 165 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from criptogus/agent-evolve-network at commit d19b920, republished under its CC-BY-SA-4.0 licence (© criptogus). 165 words, ~564 tokens.
Download SKILL.mdSave it as
.claude/skills/llm-finetuning-strategist/SKILL.md (or your agent's skills folder).- name
- llm-finetuning-strategist
- description
- Plans fine-tuning runs (LoRA/QLoRA/full) with dataset curation, hyperparams, and eval — picks SFT vs DPO vs RLHF. Use when the user asks for llm fine-tuning strategist work, or mentions llm, finetuning, strategist.
- version
- 0.1.0
- license
- CC-BY-SA-4.0
- homepage
- https://superagentskill.com/marketplace/llm-finetuning-strategist
- source
- Super Agent Skill (SAK)
LLM Fine-Tuning Strategist
Use to decide if and how to fine-tune. Outputs a runnable plan with data prep, base model, training config, compute estimate, and eval plan.
Instructions
You are a fine-tuning lead. For each task: (1) decide if fine-tuning is even the right answer vs prompting/RAG, (2) pick base model + technique (SFT, LoRA, QLoRA, DPO), (3) specify dataset format + size + curation steps, (4) hyperparams + compute estimate, (5) eval set with held-out + adversarial prompts.
Always
- Follow the section order specified in the system prompt.
Never
- Invent APIs, URLs, or facts not grounded in the input.
Examples
Choose a method
Input:
1k labeled support replies; want on-brand tone on a 7B model, small budget.Expected output:
Recommends LoRA SFT over full FT (data + budget), dataset format, key hyperparams (rank, lr, epochs), an eval set held out, and a stop criterion. Flags DPO as a later step if preference data appears.SFT vs DPO vs RLHF
Input:
When should I use DPO instead of SFT?Expected output:
SFT to teach the behavior; DPO when you have paired better/worse responses to sharpen preferences; RLHF only with a reward model + scale. Recommends SFT→DPO for most teams.Trust & telemetry
This skill is graded on the Super Agent Skill network: format, substance and adversarial (prompt-injection) testing produce a public Trust Score.
- Trust Score & evidence: https://superagentskill.com/marketplace/trust/llm-finetuning-strategist
- Skill page: https://superagentskill.com/marketplace/llm-finetuning-strategist
- Live version (always current) via MCP: https://superagentskill.com/api/mcp
Reinstall or update with npx skills update, or pull the live graded version with
npx super-agent install llm-finetuning-strategist.
© criptogus, CC-BY-SA-4.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/llm-finetuning-strategist of criptogus/agent-evolve-network.
Open the folder on GitHubat commit d19b920
Compare with similar skills
LLM Finetuning Strategist next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| LLM Finetuning Strategist this skillcriptogus/agent-evolve-network | 288 | — | ~564 | Automated safety check: Pass | CC-BY-SA-4.0 | |
| Peft Fine TuningOrchestra-Research/AI-Research-SKILLs | 13k | 9 repos | ~3.1k | Automated safety check: Pass | MIT | |
| Hugging Face LLM Trainerhuggingface/skills | 11k | 3 repos | ~7.2k | Automated safety check: Pass | Apache-2.0 | |
| Sentence-Transformers Training Routerhuggingface/skills | 11k | 1 repos | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Dataset Evaluationawslabs/agent-plugins | 915 | 2 repos | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| Train RlOpenPipe/ART | 11k | — | ~2.4k | Automated safety check: Pass | Apache-2.0 |
Similar skills
- Official
Hugging Face LLM Trainer
huggingface/skills
Trains or fine-tunes language and vision models with TRL or Unsloth on Hugging Face Jobs cloud GPUs, then converts the results to GGUF.
- Official
Sentence-Transformers Training Router
huggingface/skills
Routes a sentence-transformers training task to the right model type and required reference docs and example scripts, covering bi-encoders, rerankers, sparse and multi-vector models.
- Official
Dataset Evaluation
awslabs/agent-plugins
Validates dataset formatting and quality for SageMaker model fine-tuning (SFT, DPO, or RLVR).
Train Rl
OpenPipe/ART
RL training reference for the ART framework. An agent skill from OpenPipe/ART.
Qwopus27b Rl Training
R6410418/Jackrong-llm-finetuning-guide
Prepare, validate, launch-plan, monitor, resume, and stop configurable Qwopus 27B reinforcement-learning workflows for GRPO or GSPO.
More from criptogus/agent-evolve-network
All 107 skills in this repoBrand Research
criptogus/agent-evolve-network
Kickoff research for a brand you haven't worked on before — web research, existing-ad analysis from the Meta Ad Library, editorial-grammar profiling, sourced + AI-generated brand assets, hook/CTA…
Create Apple Notes Video Ad
criptogus/agent-evolve-network
Produce a 9:16 social-native ad recreating the iPhone Apple Notes typing experience — the note begins with 1–2 visible lines, then progressively types additional paragraphs character-by-character…
Create Chatgpt Video Ad
criptogus/agent-evolve-network
Produce a 9:16 social-native ad that recreates a ChatGPT mobile chat — user types in the composer with the iOS keyboard visible, taps send, keyboard slides down, header right-cluster swaps…
Create Imessage Video Ad
criptogus/agent-evolve-network
Produce a 9:16 social-native ad that recreates an iMessage conversation reveal — bubbles pop in over time, composer types char-by-char, real Apple iMessage SFX hit on every send/receive, music bed…
Cloud Misconfig Auditor
criptogus/agent-evolve-network
Audits AWS, GCP and Azure environments (and matching IaC) for excessive permissions, public exposure, weak encryption defaults and missing logging.
Cloudflare Workers Expert
criptogus/agent-evolve-network
Builds and debugs Cloudflare Workers, Durable Objects, KV, R2, D1, and Queues with edge-correct patterns.
Related
Categories
Questions about LLM Finetuning Strategist
What does LLM Finetuning Strategist do?
Plans fine-tuning runs (LoRA/QLoRA/full) with dataset curation, hyperparams, and eval — picks SFT vs DPO vs RLHF. LLM Finetuning Strategist is an agent skill from criptogus/agent-evolve-network. Plans fine-tuning runs (LoRA/QLoRA/full) with dataset curation, hyperparams, and eval — picks SFT vs DPO vs RLHF.
When should I use LLM Finetuning Strategist?
LLM Finetuning Strategist fits situations like: the user asks for llm fine-tuning strategist work; tasks that involve Fine-tuning.
How do I install LLM Finetuning Strategist in Claude Code?
Run `npx skills add criptogus/agent-evolve-network --skill llm-finetuning-strategist -a claude-code`. Or copy the skill folder (skills/llm-finetuning-strategist in criptogus/agent-evolve-network) into .claude/skills/llm-finetuning-strategist in your project. Claude Code loads it when a task matches its description.
How do I install LLM Finetuning Strategist in Codex?
Run `npx skills add criptogus/agent-evolve-network --skill llm-finetuning-strategist -a codex`. Or copy the skill folder (skills/llm-finetuning-strategist in criptogus/agent-evolve-network) into .agents/skills/llm-finetuning-strategist in your project. Codex loads it when a task matches its description.
Can I use LLM Finetuning Strategist in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add criptogus/agent-evolve-network --skill llm-finetuning-strategist -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/llm-finetuning-strategist, .gemini/skills/llm-finetuning-strategist, .github/skills/llm-finetuning-strategist and .opencode/skills/llm-finetuning-strategist in your project.
What does LLM Finetuning Strategist need to run?
Going by SKILL.md and its folder, LLM Finetuning Strategist needs the command-line tools its instructions call (npx). Our summary lists: Node.js.
Does LLM Finetuning Strategist access the network?
SKILL.md names 1 domain. As links in the text: superagentskill.com. This is read from the text; nothing was executed.
Is LLM Finetuning Strategist safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does LLM Finetuning Strategist use?
LLM Finetuning Strategist is published under the CC-BY-SA-4.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does LLM Finetuning Strategist use?
About 564 tokens (SKILL.md is roughly 2.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to LLM Finetuning Strategist?
Skills that share tags, products or a category with LLM Finetuning Strategist: Peft Fine Tuning (Orchestra-Research/AI-Research-SKILLs, 13k stars), Hugging Face LLM Trainer (huggingface/skills, 11k stars), Sentence-Transformers Training Router (huggingface/skills, 11k stars) and Dataset Evaluation (awslabs/agent-plugins, 915 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains LLM Finetuning Strategist?
criptogus (a GitHub user) maintains it in criptogus/agent-evolve-network, which has 288 GitHub stars. The repository holds 107 skills in this directory. The repository was last updated on September 9, 2026.
Source: criptogus/agent-evolve-network on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.