Train task-specific small language models (SLMs) using the Distil Labs CLI and platform. Activate this skill when the user asks about: distil labs, distil CLI, the distil command, training small language models, knowledge distillation, creating SLMs from production traces, data preparation for model training, fine-tuning student models from teacher models, deploying trained SLMs, model evaluation metrics, task-specific model training, classification/QA/tool-calling model training, synthetic data generation for training, or any question about the distil platform, its configuration, or its workflows. Also activate when the user mentions: distil model, distil login, distil register, uploading training data, teacher evaluation, model retuning, model deployment with llama-cpp or vLLM, or when working with config.yaml / jobdescription.json / train.csv files for model training.
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategoryEngineeringStars0
About this skill
Train task-specific small language models (SLMs) using the Distil Labs CLI and platform. Activate this skill when the user asks about: distil labs, distil CLI, the distil command, training small language models, knowledge distillation, creating SLMs from production traces, data preparation for model training, fine-tuning student models from teacher models, deploying trained SLMs, model evaluation metrics, task-specific model training, classification/QA/tool-calling model training, synthetic data generation for training, or any question about the distil platform, its configuration, or its workflows. Also activate when the user mentions: distil model, distil login, distil register, uploading training data, teacher evaluation, model retuning, model deployment with llama-cpp or vLLM, or when working with config.yaml / jobdescription.json / train.csv files for model training.
Quick start
Copy the install prompt. Use the green button above this README.
Send it to your agent. Paste it into your coding agent’s chat and send.
Review the setup. Your agent checks the skill’s instructions, requirements, and installation scope.
Train task-specific small language models (SLMs) using the Distil Labs CLI and platform. Activate this skill when the user asks about: distil labs, distil CLI, the distil command, training small language models, knowledge distillation, creating SLMs from production traces, data preparation for model training, fine-tuning student models from teacher models, deploying trained SLMs, model evaluation metrics, task-specific model training, classification/QA/tool-calling model training, synthetic data generation for training, or any question about the distil platform, its configuration, or its workflows. Also activate when the user mentions: distil model, distil login, distil register, uploading training data, teacher evaluation, model retuning, model deployment with llama-cpp or vLLM, or when working with config.yaml / job_description.json / train.csv files for model training.
About this listing
Category
Engineering
Reported license
Apache-2.0
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.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLI