yolo-export skillA
yolo-export is agent-read markdown (skill) from ultralytics/skills: Use when exporting or deploying Ultralytics YOLO models in Platform or code — the Platform Export tab and yolo export/model.export() for ONNX, TensorRT, CoreML, Core AI, OpenVINO, LiteRT, NCNN, ExecuTorch, and NPUs (RKNN, QNN, Hailo, Ascend, IMX, Axelera, DeepX), FP16/INT8 quantization, benchmarking, and non-Python runtimes. For inference with .pt weights or Platform endpoints, see yolo-inference..
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
# Export, quantization & deployment
## Fastest route: export in Platform
Open a completed model's **Export** tab, select one of the 20 formats, configure its
arguments, and click **Start Export**. Platform runs CPU exports directly and asks for a
target GPU where the format requires one (notably TensorRT); download the artifact when
the job completes. Match TensorRT's selected GPU family and software environment to the
deployment target, just as with a local engine build.
Use Platform when you do not want to install each exporter toolchain locally. Use the
Python/CLI path below for custom calibration, repeatable automation, local hardware
builds, or immediate parity validation. See
[Platform model export](https://docs.ultralytics.com/platform/train/models#export-model).
## Quickstart
```python
from ultralytics import YOLO
model = YOLO("runs/detect/train/weights/best.pt")
path = model.export(format="onnx") # returns the exported file/dir path
```
```bash
yolo export model=best.pt format=onnx
```
Exports load straight back into `YOLO()` for predict/val — same API:
```python
model = YOLO("best.onnx") # or best.engine, best_openvino_model/, ...
```
…Read the whole file at its exact version.
How to install
mdr add ultralytics/skills/yolo-export@git:20260904.9c3b8ecmdr add ultralytics/skills/yolo-export@sha256:fe071aa1472c295fPin 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_odkflt4bs2lnosdq)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260904.9c3b8ec latest | 2026-09-04 | 9c3b8ec | 11,517 B | A | view · diff |
| git:20260820.dcee0db | 2026-08-20 | dcee0db | 11,017 B | A | view · diff |
| git:20260814.05a799c | 2026-08-14 | 05a799c | 11,018 B | A | view · diff |
| git:20260811.e35dbcc | 2026-08-11 | e35dbcc | 10,750 B | A | view · diff |
| git:20260811.47343d9 | 2026-08-11 | 47343d9 | 9,989 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 (11517 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_odkflt4bs2lnosdq GET https://markdownregistry.com/api/v1/resolve?ref=ultralytics/skills/yolo-export GET https://markdownregistry.com/api/v1/blob/fe071aa1472c295fb9f8013c0a39637f3c2812b8438800afe4bde80f3db869cc
Your agent 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.