FreeSkills
Commits, branches and sync with the but CLI
- 361361 downloads
- 198198 likes
- 103103 saves
Works with
- Claude Code
- Codex
- Cursor
- and 3 more
Fine-tune CLIP and deploy to ONNX or TensorRT v1.0.0
Use this resource to fine-tune CLIP on your image-caption pairs and export it for inference
New
- 419 downloads
- 250 likes
- 118 saves
Free
Install with the CLI
In a terminal, from the folder you want:
npx --yes palatekit@latest install clip-vision-language-finetuneWith 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 writes the training, evaluation, export or deployment spec for CLIP, runs the action you choose and checks the results. It does not run the iterative loop that improves weak attributes, which belongs to tao-run-deft-pas.
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
- SKILL.md : actions, requirements and procedure
- references/clip-peft.md : LoRA tuning and regularization
- references/spec_template_export.yaml : export spec template
Good fit for
- You want to find images from a text phrase
- You have image-caption pairs and want to adapt CLIP
Not for
Tags
- clip
- image-text
- fine-tuning
- onnx
- tensorrt
About
You say
“Fine-tune CLIP on my product image-caption pairs and export it to ONNX.”
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 fine-tune CLIP on your image-caption pairs and export it for inference
- Review and adjust the result
Content preview
Files
- BENCHMARK.md7 KB
- config/skillspector-baseline.yaml0.8 KB
- evals/evals.json0.8 KB
- LICENSE11.3 KB
- NOTICE-PALATEKIT.md0.5 KB
- references/clip-peft.md7.1 KB
- references/error-patterns.md5.3 KB
- references/pas-metrics.md1.3 KB
- references/skill_info.yaml5 KB
- references/spec_template_deploy.yaml0.6 KB
- references/spec_template_evaluate.yaml1.5 KB
- references/spec_template_export.yaml1.5 KB
- references/spec_template_train.yaml1.8 KB
- references/spec_template.yaml2.6 KB
- references/spec-param-inference.md2.5 KB
- references/standalone-setup.md2.1 KB
- references/tao-deploy-clip.md5.9 KB
- references/tao-deploy-clip.skill_info.yaml2.2 KB
- schemas/evaluate.schema.json27.4 KB
- schemas/export.schema.json28.2 KB
- schemas/manifest.json4.8 KB
- schemas/train.schema.json32.1 KB
- skill-card.md4.4 KB
- SKILL.md19.7 KB
- skill.oms.sig8.8 KB
Origin and licence
Listed unmodified
- Author
- nvidia
- Source
- github.com/nvidia/skills/tree/ca116d60beafe1b4459f0ab790b7b450912c56b0/skills/tao-finetune-clip
- Licence
- Apache-2.0
Notice
« tao-finetune-clip » (nvidia, Apache-2.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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