---

name: "conversion" description: "Routes LightX2V LoRA extraction, LoRA merging, dummy-meta export, and weight-format conversion preparation workflows." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Conversion

Use this sub-skill for checkpoint surgery, LoRA preparation, dummy-meta export, and other weight-preparation workflows that sit beside the main generation stack.

Typical triggers

• "extract a LoRA from two checkpoints"
• "merge LoRA weights into a base model"
• "export dummy-meta safetensors"
• "how do I convert or quantize weights?"
• "what are the LoRA key conventions?"

Read first

• references/formats.md for the weight-format and LoRA naming conventions.
• references/workflows.md for the common conversion and preparation flows.
• references/troubleshooting.md for CUDA extension, key-mapping, and shape-mismatch failures.
• ../../references/troubleshooting.md for cross-cutting package and environment failures.

What belongs here

Include:

• LoRA extraction from a source / target checkpoint pair
• LoRA merging back into a base checkpoint
• dummy-meta safetensors export
• weight-format and metadata preparation for LightX2V deployment
• quantization planning and conversion guidance when the tooling is light enough to document safely

Exclude or route elsewhere:

• direct generation → sub-skills/inference/
• HTTP server and queue management → sub-skills/serving/
• controller / encoder / transformer / decoder deployment → sub-skills/disagg/
• training workflows → out of scope for this skill graph

Bundled helpers

• scripts/extract_lora.py
• scripts/merge_lora.py
• scripts/export_dummy_meta.py

The full conversion utility is documented in the references but is intentionally left reference-only because it depends on heavier optional CUDA extension build paths and broad model-family branches.

Safe starting checks

• python scripts/check_install.py
• python sub-skills/conversion/scripts/export_dummy_meta.py --help
• python sub-skills/conversion/scripts/extract_lora.py --help
• python sub-skills/conversion/scripts/merge_lora.py --help

Guidance style

When you answer from this route, name:

• the source and target checkpoint layout
• the LoRA format or diff format involved
• whether the user wants extraction, merging, or metadata-only export
• whether the full converter is actually needed or a lightweight helper is enough
• the build prerequisites if quantization or CUDA extensions are involved

Decision points

When routing a weight-preparation request, choose the narrowest safe helper:

• metadata only → export_dummy_meta.py
• source/target delta extraction → extract_lora.py
• applying an extracted or diff-style LoRA back into a base checkpoint → merge_lora.py
• broader architecture conversion or quantization planning → reference the full converter, but keep it reference-only unless the user explicitly needs that heavier path

Common reminders:

• safetensors and pytorch are the two supported source formats in the bundled helpers
• LoRA suffixes vary by model family, so mention the expected naming convention when the user asks about missing keys
• --diff-only is the safest answer when the user only needs raw deltas
• the dummy-meta helper is useful when the config only needs tensor metadata and not the full payload
• the full converter depends on heavier optional CUDA extension build paths, so it stays out of the bundled runtime surface for now

If a request is really about runtime generation or serving, route away from this sub-skill rather than forcing it into conversion language.