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model-patch

Merge a base HF model dir with an extra HF model dir by index diff — take tensors only present in extra, append them to a new output dir in HF-standard shard layout. Base wins on overlap.

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SKILL.md
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name
model_patch
description
Merge a base HF model dir with an extra HF model dir by index diff — take tensors only present in extra, append them to a new output dir in HF-standard shard layout. Base wins on overlap.
# model_patch Produce ``out = base ∪ (extra \ base)`` at the **tensor level**, by diffing the two ``model.safetensors.index.json`` files. Useful when ``extra`` is a sibling checkpoint (different training run, fine-tune, or fp8 conversion) that holds a few tensors the base is missing — e.g. an updated head, a newly-added MTP block, or auxiliary projections — and you want a self-contained merged dir without re-running the whole conversion pipeline. Overlap rule: **base wins**. Any tensor present in both indexes is taken from ``base``; the corresponding entry in ``extra`` is ignored. ## Layout ``` .claude/skills/model_patch/ ├── SKILL.md # this file └── model_patch.py # CLI + library ``` ## Usage ```bash python model_patch.py \ --base /path/to/base-model \ --extra /path/to/extra-model \ --out /path/to/merged-model ``` ## What it writes - ``model-{i:05d}-of-{N:05d}.safetensors`` shards (total ``N`` = base shards + newly-packed shards holding the extra-only tensors) - a fresh ``model.safetensors.index.json`` - **every non-tensor file from ``base``** — ``config.json``, tokenizer files, modeling/configuration ``.py``, ``generation_config.json``, README, etc. — copied verbatim so ``out`` is loadable on its own. Subdirectories are copied recursively. Existing entries in ``out`` are overwritten. ``extra``'s aux files are deliberately **not** copied. The skill's overlap rule is "base wins" at the tensor level, and that extends to configs: extra often carries engine-specific edits or modality keys that don't match the tensor topology we keep. If you need fields from ``extra``'s ``config.json`` (e.g. a new modality), merge them into ``out/config.json`` as a separate, explicit step. ## How shards are produced - **Base shards**: re-emitted under the new ``-of-N`` total. By default the bytes are fully copied so ``out`` is independent of ``base``. Pass ``--hardlink`` to use ``os.link`` instead (fast, but the two trees share inodes — editing one mutates the other; deleting one keeps the other intact since hardlinks are symmetric). - **Extra-only tensors**: greedily bin-packed into new shards of at most ``--shard-size-gb`` GiB (default 4), appended after the base shards. So a base with 12 shards plus 5 GB of extra-only tensors yields: ``model-00001-of-00014.safetensors`` … ``model-00012-of-00014.safetensors`` (copies of the base shards) and ``model-00013-of-00014.safetensors`` / ``model-00014-of-00014.safetensors`` (freshly written, containing only the extra tensors). ## When to use this skill | Situation | Use this? | | -------------------------------------------------------------------------------------- | --------- | | ``extra`` contains a few tensors ``base`` is missing; everything else is identical. | Yes | | You need to merge two checkpoints whose overlapping tensors **differ** in value. | No — this skill silently keeps base; you probably want a manual decision per key. | | ``extra`` is a full quantization of ``base`` and you want the quantized weights. | No — use ``model_normalize`` with ``--reference extra`` instead. | | You want a single ``model.safetensors`` instead of standard shards. | No — repack downstream. | ## Required usage protocol (mandatory for the agent) Before invoking ``model_patch.py``: 1. Confirm the three paths (``--base``, ``--extra``, ``--out``) with the user via ``AskUserQuestion``. Never infer them from earlier conversation. 2. Show the user the **diff summary** before writing, by reading the two ``model.safetensors.index.json`` files and reporting: - number of tensors in base - number of tensors in extra - number of extra-only keys that will actually be added - number of overlapping keys that will be dropped from extra 3. Ask the user to confirm those numbers before launching the run. After a successful run, **do not** ask the user where the output should go — ``--out`` is already the final destination the user named. Just report what landed there (shard count, index path, total size, and that base's aux files were mirrored over). Unlike ``model_normalize``, ``model_patch`` has no staging-area concept: there is no temp dir, and the caller already made the placement decision when they passed ``--out``. If the user wanted any of ``extra``'s aux files (e.g. a ``config.json`` that documents a new modality), call that out — those are not copied by the skill and must be merged in by hand.
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