FreeSkills
Commits, branches and sync with the but CLI
- 361361 downloads
- 198198 likes
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Works with
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- Codex
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TensorFlow Serving setup v1.0.0
Use this resource to deploy a TensorFlow model behind an inference server
New
- 419 downloads
- 224 likes
- 168 saves
Free
Install with the CLI
In a terminal, from the folder you want:
npx --yes palatekit@latest install tensorflow-serving-setupWith 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 model format, the server configuration and the prediction API call. You get an inference service ready to test.
Mostly picked by
Updated November 2, 2026
Previews
Details
- Install guides
- Generates with
- Your agent's model
- Licence
- MIT
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What you get
- SKILL.md: configuration steps and good practices
- SKILL.md: request examples and expected output
Good fit for
- Your TensorFlow model is called from several applications
- You want to serve several versions of the same model
Not for
Tags
- tensorflow
- serving
- inference
- api
About
You say
“Deploy my TensorFlow fraud detection model with TensorFlow Serving and give me a sample call.”
Skill published by Jeremy Longshore <jeremy@intentsolutions.io> under the MIT 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 deploy a TensorFlow model behind an inference server
- Review and adjust the result
Content preview
Files
- LICENSE1.1 KB
- NOTICE-PALATEKIT.md0.6 KB
- SKILL.md2.3 KB
Origin and licence
Listed unmodified
- Author
- Jeremy Longshore <jeremy@intentsolutions.io>
- Source
- github.com/jeremylongshore/tons-of-skills-marketplace/tree/ab85a061f7bcc039dac13ee193de7a4cd4388571/skills/08-ml-deployment/tensorflow-serving-setup
- Licence
- MIT
Notice
« tensorflow-serving-setup » (Jeremy Longshore <jeremy@intentsolutions.io>, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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