---

name: conversion-and-maintenance description: "Use Diffusers CLI helpers, checkpoint and format conversion scripts, ONNX export guidance, and repository maintenance checks for copied code, dummy objects, dependencies, style, and safe edits." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Conversion And Maintenance

Use this sub-skill when the task is about converting weights or maintaining the Diffusers repository rather than running inference, training, or adapter composition.

Route Here For

• diffusers-cli env, fp16_safetensors, and custom_blocks command discovery, environment reports, Hub PR conversion helper behavior, or modular custom block packaging.
• Stable Diffusion original checkpoint to Diffusers conversion, Diffusers model to original SD/SDXL single-file conversion, LoRA safetensors merge/extraction scripts, and ONNX export scripts.
• Single-file and local/offline conversion planning, including from_single_file, config, local_files_only, .safetensors versus .ckpt, and avoiding accidental Hub pushes.
• Repo maintainer work involving copied-code propagation, generated dummy files, optional dependency registration, import guards, make style, and focused tests.

Route Elsewhere

• End-to-end generation, pipeline loading for inference, device placement during generation, or serving: use ../pipelines-and-inference/SKILL.md.
• Adapter API usage such as load_lora_weights, set_adapters, fuse_lora, textual inversion, IP-Adapter, T2I-Adapter, or ControlNet loading: use ../adapters-and-loaders/SKILL.md.
• Training or fine-tuning recipes: use ../training-recipes/SKILL.md.
• Scheduler algorithm changes without conversion/maintenance context: use ../schedulers/SKILL.md.

Fast Workflow

1. Classify the request as CLI probe, conversion command planning, ONNX export, single-file/local format handling, or repository maintenance.
2. For CLI/environment questions, run python scripts/diffusers_cli_probe.py --help and then a safe probe such as python scripts/diffusers_cli_probe.py env.
3. For conversion tasks, run python scripts/conversion_command_builder.py --help and emit a command skeleton for the right family before touching weights.
4. Use references/conversion-workflows.md to choose required flags, safety checks, and no-push/offline behavior.
5. Use references/cli-and-maintenance.md for diffusers-cli, copied-code, dummy-object, optional dependency, style, and focused test rules.
6. If failures mention missing optional dependencies, CPU/GPU/dtype mismatch, missing local configs, unsafe file formats, bad LoRA prefixes, or copy drift, use references/troubleshooting.md.

Key Rules

• Prefer local output directories and explicit paths; do not push to the Hub unless the user explicitly asks for it.
• Prefer .safetensors for untrusted weights; .ckpt uses pickle-style loading and can be unsafe.
• For local/offline single-file work, provide a local config directory and local_files_only=True rather than relying on Hub inference.
• Choose device and dtype together: CPU for inspection/skeletons, CUDA for fp16-heavy conversion/export, and avoid fp16 ONNX export without CUDA.
• Do not edit # Copied from ... blocks directly unless intentionally breaking the copy link; normally edit the source and run make fix-copies.

References

• Conversion workflows: references/conversion-workflows.md
• CLI and maintenance: references/cli-and-maintenance.md
• Troubleshooting: references/troubleshooting.md
• CLI probe: scripts/diffusers_cli_probe.py
• Conversion command builder: scripts/conversion_command_builder.py