From training-hub
Runs LLM training jobs from saved configurations with environment detection and result reporting.
How this skill is triggered — by the user, by Claude, or both
Slash command
/training-hub:training-guideThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Execute LLM training using a saved configuration.
Execute LLM training using a saved configuration.
"${CLAUDE_PLUGIN_ROOT}/scripts/th_detect.sh"
library=missing or config=missing: invoke the setup-guide skill.gpu=unavailable: warn that training requires CUDA-capable GPUs.library=installed, config=found)Proceed to Step 2.
Run the training script with any user-provided overrides:
"${CLAUDE_PLUGIN_ROOT}/scripts/th_train.sh" $ARGUMENTS
If training failed, consult the training-hub-guide skill for troubleshooting (OOM, loss interpretation, backend-specific issues).
Remind the user they can visualize training loss with training_hub.plot_loss().
npx claudepluginhub red-hat-ai-innovation-team/training_hub --plugin training-hubGuides users through setting up LLM training with training_hub: environment detection, installation, GPU checks, and configuration.
Autonomous LLM training optimization loop for single-GPU. Runs 5-minute experiments measuring val_bpb, keeps improvements or reverts. Automates hyperparameter search and experiment tracking.
Trains or fine-tunes LLMs/VLMs on Hugging Face cloud GPUs using TRL (SFT, DPO, GRPO, reward modeling) or Unsloth, with GGUF conversion for local deployment. No local GPU setup needed.