FreeSkills
Commits, branches and sync with the but CLI
- 361361 downloads
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Works with
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OneFormer training for universal segmentation v1.0.0
Use this resource to train and deploy a OneFormer universal segmentation model with TAO
New
- 545 downloads
- 226 likes
- 202 saves
Free
Install with the CLI
In a terminal, from the folder you want:
npx --yes palatekit@latest install oneformer-universal-segmentation-trainingWith no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.
First time: connect the CLI with
npx --yes palatekit@latest loginThe agent sets up the train, evaluate, export, quantize and inference specs for OneFormer, then checks the required datasets. For TensorRT actions, it points to the deploy templates provided with the skill.
Mostly picked by
Updated November 2, 2026
Previews
Details
- Install guides
- Generates with
- Your agent's model
- Licence
- Apache-2.0
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What you get
- references/spec_template_export.yaml: export spec
- references/spec_template_quantize.yaml: quantization spec
- references/skill_info.yaml: container and action information
Good fit for
- You want one model for panoptic, instance and semantic segmentation
- You must export and quantize a trained OneFormer model
Not for
Tags
- oneformer
- segmentation
- panoptic
- tao
About
You say
“Prepare the export spec for my trained OneFormer model.”
Skill published by nvidia under the Apache-2.0 license, delivered in its original version.
Show moreShow less
How to use it
- Install the skill in your agent's skills folder
- Ask your agent to train and deploy a OneFormer universal segmentation model with TAO
- Review and adjust the result
Content preview
Files
- BENCHMARK.md7.1 KB
- config/skillspector-baseline.yaml0.8 KB
- evals/evals.json0.8 KB
- LICENSE11.3 KB
- NOTICE-PALATEKIT.md0.5 KB
- references/skill_info.yaml9.8 KB
- references/spec_template_deploy_evaluate.yaml0.5 KB
- references/spec_template_deploy_gen_trt_engine.yaml0.3 KB
- references/spec_template_deploy_inference.yaml0.5 KB
- references/spec_template_evaluate.yaml4.9 KB
- references/spec_template_export.yaml5 KB
- references/spec_template_gen_trt_engine.yaml5 KB
- references/spec_template_inference.yaml4.9 KB
- references/spec_template_quantize.yaml4.7 KB
- references/spec_template_train.yaml4.7 KB
- references/tao-deploy-oneformer.md6.3 KB
- references/tao-deploy-oneformer.skill_info.yaml3.8 KB
- schemas/evaluate.schema.json75.3 KB
- schemas/export.schema.json76 KB
- schemas/gen_trt_engine.schema.json77.9 KB
- schemas/inference.schema.json76 KB
- schemas/manifest.json18.9 KB
- schemas/quantize.schema.json72.5 KB
- schemas/train.schema.json72.5 KB
- skill-card.md4.6 KB
- SKILL.md19.8 KB
- skill.oms.sig9.4 KB
Origin and licence
Listed unmodified
- Author
- nvidia
- Source
- github.com/nvidia/skills/tree/ca116d60beafe1b4459f0ab790b7b450912c56b0/skills/tao-train-oneformer
- Licence
- Apache-2.0
Notice
« tao-train-oneformer » (nvidia, Apache-2.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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