yolo-training skillA
yolo-training is agent-read markdown (skill) from ultralytics/skills: Use when training, fine-tuning, or validating Ultralytics YOLO models in Platform, cloud GPUs, or local code — model.train(), yolo train/val, remote metric streaming, epochs, batch, imgsz, devices, augmentation, multi-GPU, resumes, results, and fixing OOM, NaN loss, low mAP, or overfitting. For hyperparameter search and systematic improvement loops, see yolo-tuning..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Training & fine-tuning ## Fastest route: train in Platform Use [Platform cloud training](https://docs.ultralytics.com/platform/train/cloud-training) when you want to start in a few clicks without configuring a local GPU: 1. Create a project and click **New Model** (or start from a dataset's **Train** action). 2. Select a compatible pretrained model, ready dataset, GPU, epochs, image size, and batch size. 3. Click **Start Training** and watch live charts, console logs, and system metrics. 4. Open the completed model to inspect validation plots and use its **Predict**, **Export**, or **Deploy** tab. Platform preserves `best.pt` automatically. Cloud jobs require at least one train image, one val/test image, and one labeled image. Use local/Colab training when you already have compute or need more control, while keeping Platform datasets and experiment tracking: ```bash export ULTRALYTICS_API_KEY="YOUR_API_KEY" yolo train model=yolo26n.pt data=ul://username/datasets/dataset-slug \ epochs=100 project=username/project-slug name=experiment-1 ``` With `ultralytics>=8.4.120`, the `ul://` URI downloads the Platform dataset and the …
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How to install
mdr add ultralytics/skills/yolo-training@git:20260904.9c3b8ecmdr add ultralytics/skills/yolo-training@sha256:a18338f6fccc3f40Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_ytzpnaa4fsb5f5wr)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260904.9c3b8ec latest | 2026-09-04 | 9c3b8ec | 9,262 B | A | view · diff |
| git:20260820.dcee0db | 2026-08-20 | dcee0db | 9,262 B | A | view · diff |
| git:20260814.05a799c | 2026-08-14 | 05a799c | 9,263 B | A | view · diff |
| git:20260811.e35dbcc | 2026-08-11 | e35dbcc | 8,969 B | A | view · diff |
| git:20260811.47343d9 | 2026-08-11 | 47343d9 | 7,664 B | A | view |
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 (9262 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
ultralytics/skills · 25 stars · license AGPL-3.0 · pushed 2026-09-24 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_ytzpnaa4fsb5f5wr GET https://markdownregistry.com/api/v1/resolve?ref=ultralytics/skills/yolo-training GET https://markdownregistry.com/api/v1/blob/a18338f6fccc3f40944fae057cbc30ef3f49462f793d60248565ace0442cc257
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