Agent SkillsAtlasBETASign in
Back to directory

Rlat Build on Kaggle

Agent skill
1 skill
READMEOverview ↓

Build large rlat knowledge models (.rlat files) on Kaggle's free T4 GPU when the local machine has no GPU or encoding would take too long on CPU. Walks the user through Kaggle account + CLI setup, builds a kernel script that installs rlat[build,ann], sparse-clones (or uploads) source, encodes the corpus on T4, writes a remote-mode .rlat back, and pulls the artefact home. Trigger when the user mentions Kaggle, "free GPU", "build remotely", "no GPU here", a corpus too large to encode locally (~10K+ passages on CPU), or wants to rebuild several .rlat files in one batch. Not for: small corpora that finish in minutes on CPU; users who already have a CUDA GPU (just pip install rlat[build] and run rlat build locally).

Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI

Supported by the Atlas install prompt. Skill-specific requirements vary.

Skill stats

Skills1CategoryGeneralStars0

About this skill

Build large rlat knowledge models (.rlat files) on Kaggle's free T4 GPU when the local machine has no GPU or encoding would take too long on CPU. Walks the user through Kaggle account + CLI setup, builds a kernel script that installs rlat[build,ann], sparse-clones (or uploads) source, encodes the corpus on T4, writes a remote-mode .rlat back, and pulls the artefact home. Trigger when the user mentions Kaggle, "free GPU", "build remotely", "no GPU here", a corpus too large to encode locally (~10K+ passages on CPU), or wants to rebuild several .rlat files in one batch. Not for: small corpora that finish in minutes on CPU; users who already have a CUDA GPU (just pip install rlat[build] and run rlat build locally).

Quick start

  1. Copy the install prompt. Use the green button above this README.
  2. Send it to your agent. Paste it into your coding agent’s chat and send.
  3. Review the setup. Your agent checks the skill’s instructions, requirements, and installation scope.

Installation guide →

Review, license & listing details
Review the source before using this skill

This is an imported listing. We haven’t certified its safety, license, or compatibility. Skills may include executable scripts.

Automated security scan: Partial

Only SKILL.md was scanned. Supporting files and scripts were not checked. No safety grade has been assigned.

0 potential findings · Scanned 11/4/2026 · Scanner 0.2.1

Content SHA-256: ad35799d69adef06f30051b71d058a95696971af99b1b5b0b63a4be59bbc3e60

About scan coverage and limitations
Original listing metadata

Original name

rlat-build-on-kaggle

Original description

Build large rlat knowledge models (.rlat files) on Kaggle's free T4 GPU when the local machine has no GPU or encoding would take too long on CPU. Walks the user through Kaggle account + CLI setup, builds a kernel script that installs rlat[build,ann], sparse-clones (or uploads) source, encodes the corpus on T4, writes a remote-mode .rlat back, and pulls the artefact home. Trigger when the user mentions Kaggle, "free GPU", "build remotely", "no GPU here", a corpus too large to encode locally (~10K+ passages on CPU), or wants to rebuild several .rlat files in one batch. Not for: small corpora that finish in minutes on CPU; users who already have a CUDA GPU (just `pip install rlat[build]` and run `rlat build` locally).

About this listing

Category
General
Reported license
Not specified
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
KEEP EXPLORING

Related packs & skills

Browse category →

Finding related packs and skills…

Rlat Build on Kaggle | Agent Skills Atlas