---

name: model-tools description: "Operate AutoTrain Advanced utility commands for LLM adapter merging and Kohya LoRA conversion." disable-model-invocation: true metadata: disco-role: operating parent-skill: autotrain-advanced license: Apache 2.0

AutoTrain model tools

Use this sub-skill for autotrain tools commands and standalone model-artifact utilities.

Supported commands

autotrain tools merge-llm-adapter --help
autotrain tools convert_to_kohya --help

Tool workflows:

• merge-llm-adapter loads a base causal LM, loads a PEFT adapter, merges it, then saves locally and/or pushes to Hub.
• convert_to_kohya converts a safetensors LoRA state dict through PEFT format into Kohya format.

Bundled helper scripts

• scripts/merge_llm_adapter.py — source-derived standalone wrapper for the merge function.
• scripts/convert_to_kohya.py — source-derived standalone wrapper for Kohya conversion.

Use the package CLI when the installed autotrain command is available; use the bundled scripts when a future agent needs a clear self-contained copy of the core tool logic.

Command templates

autotrain tools merge-llm-adapter \
  --base-model-path base/model-or-path \
  --adapter-path adapter/model-or-path \
  --output-folder merged-model \
  --token "$HF_TOKEN"

autotrain tools convert_to_kohya \
  --input-path adapter_model.safetensors \
  --output-path adapter_kohya.safetensors

Safety notes

• Adapter merge loads model weights and can consume significant CPU/GPU memory.
• Merge requires either --output-folder or --push-to-hub.
• Private models/adapters require a valid token.
• Kohya conversion expects a safetensors LoRA state dict, not a full model directory.

References

• references/workflows.md — exact inputs/outputs and script/CLI mapping.
• references/troubleshooting.md — load, memory, token, output, and conversion failures.