gemma-trainer SKILL.md skillA
gemma-trainer from skillmds/skillmd is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add skillmds/skillmd/gemma-trainer@git:20260919.fecc0d5Pins git:20260919.fecc0d5 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- skillmds/skillmd
- Path
plugins/agents-mcp/skills/gemma-trainer/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260919.fecc0d5, committed Sep 19, 2026
- Size
- 7,713 bytes
- Repository stars
- 250
- License
- MIT
Trigger this skill when the user wants to train, fine-tune, or adapt Gemma models (e.g. SFT, DPO, RLHF, Reward Modeling) on local hardware. Covers TRL, Unsloth, dataset preparation, validation, and GGUF/LiteRT conversion.
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
# Gemma Training and Fine-Tuning Skill ## 1. Core Principles: Local Fine-Tuning Setup When training locally, memory efficiency and execution speed are huge. Always guide the user to follow these best practices: * **Prioritize Unsloth**: For local single-GPU training, always recommend **Unsloth**. It supports Gemma 4 natively, uses up to 70% less memory, and is up to 2x faster than standard Hugging Face PEFT training. * **Fall Back to TRL**: For multi-GPU environments (using DDP/FSDP) or when Unsloth is unavailable, use Hugging Face **TRL** (`SFTTrainer`, `DPOTrainer`) coupled with **PEFT** and **bitsandbytes** (for QLoRA). * **Always use QLoRA (4-bit Quantization)**: Crucial for fitting Gemma models (like Gemma 4 12B/31B) into consumer VRAM. * **Manage Context Window & Max Length**: Although Gemma 4 supports up to a 256K context window, recommend training with a context window of 2048 to 8192 tokens locally to prevent Out-Of-Memory (OOM) errors. ## 2. Choosing the Right Training Method Help the user choose the correct workflow based on their goal: - **Supervised Fine-Tuning (SFT)**: Teaching new domains, specialized task instructions, or custom output structures. …
Read the whole file at its exact version.
How to install
mdr add skillmds/skillmd/gemma-trainer@sha256:d73853f49622b4e8The line at the top of this page pins the label git:20260919.fecc0d5, 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_b3etanao4tajn2lt)
4 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on Sep 19, 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 (7713 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
skillmds/skillmd · 250 stars · license MIT · pushed 2026-10-20 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_b3etanao4tajn2lt GET https://markdownregistry.com/api/v1/resolve?ref=skillmds/skillmd/gemma-trainer GET https://markdownregistry.com/api/v1/blob/d73853f49622b4e8a61e22096f10afecf578cd0e6e21c29b9dcb264310b3dd5a
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.