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Commits, branches and sync with the but CLI
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Mask2Former training for universal segmentation v1.0.0
Use this resource to train and deploy a Mask2Former universal segmentation model with TAO
New
- 565 downloads
- 184 likes
- 249 saves
Free
Install with the CLI
In a terminal, from the folder you want:
npx --yes palatekit@latest install mask2former-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 prepares the Mask2Former evaluation, export and TensorRT deploy specs, with the Swin backbone and the required datasets. You get configuration files to adapt to your segmentation task.
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_evaluate.yaml: evaluation spec
- references/skill_info.yaml: container and action information
Good fit for
- You want one model for panoptic, instance and semantic segmentation
- You must quantize a Mask2Former model for TensorRT
Not for
Tags
- mask2former
- segmentation
- panoptic
- tao
About
You say
“Prepare the export of my trained Mask2Former model for TensorRT.”
Skill published by nvidia under the Apache-2.0 license, delivered in its original version.
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How to use it
- Install the skill in your agent's skills folder
- Ask your agent to train and deploy a Mask2Former 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.yaml9.9 KB
- references/spec_template_deploy_evaluate.yaml0.7 KB
- references/spec_template_deploy_gen_trt_engine.yaml0.3 KB
- references/spec_template_deploy_inference.yaml0.7 KB
- references/spec_template_evaluate.yaml3.9 KB
- references/spec_template_export.yaml4 KB
- references/spec_template_gen_trt_engine.yaml4 KB
- references/spec_template_inference.yaml3.9 KB
- references/spec_template_quantize.yaml3.7 KB
- references/spec_template_train.yaml3.7 KB
- references/tao-deploy-mask2former.md6 KB
- references/tao-deploy-mask2former.skill_info.yaml3.8 KB
- schemas/evaluate.schema.json68.5 KB
- schemas/export.schema.json69 KB
- schemas/gen_trt_engine.schema.json71.6 KB
- schemas/inference.schema.json68.5 KB
- schemas/manifest.json17.8 KB
- schemas/quantize.schema.json65.8 KB
- schemas/train.schema.json65.8 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-mask2former
- Licence
- Apache-2.0
Notice
« tao-train-mask2former » (nvidia, Apache-2.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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