Comfy-Org/Wan_2.2_ComfyUI_Repackaged warn
The weights don't match the model it claims to be based on. Plus 1 minor note.
claims base: nvidia/ChronoEdit-14B-Diffusers, Wan-AI/Wan2.2-Animate-14B, alibaba-pai/Wan2.2-Fun-A14B-Control-Camera, alibaba-pai/Wan2.2-Fun-A14B-Control, alibaba-pai/Wan2.2-Fun-5B-Control, alibaba-pai/Wan2.2-Fun-5B-InP, alibaba-pai/Wan2.2-Fun-A14B-InP, alibaba-pai/Wan2.2-VACE-Fun-A14B, Wan-AI/Wan2.2-I2V-A14B, Wan-AI/Wan2.2-S2V-14B, Wan-AI/Wan2.2-T2V-A14B, Wan-AI/Wan2.2-TI2V-5B, lightx2v/Wan2.2-Distill-Loras · chat template: not found · view on Hugging Face ↗
Scan coverageStatic battery2026-08-20Weights battery2026-08-20Behavioral batteryn/adetails
| Battery | Looks at | Status |
|---|---|---|
| Static battery | Metadata & packaging | complete 2026-08-20 |
| Weights battery | Weights forensics: no GPU, no download | complete 2026-08-20256,384-token embedding scanned · 487 undertrained · lineage inconsistent |
| Behavioral battery | Live-inference differentials | n/anot applicable: image-to-video model has no text-generation surface to probe |
Ingot runs three batteries against a model. What each one checks →
Findings
Scanned 2026-08-20 · published from a community scan.
low Undertrained tokens in vocabulary (non-ASCII tail)
Embedding-norm scan flagged 487 undertrained tokens (norm < 0.3× the vocabulary median), but 0 decode to plain-ASCII strings, so exposure in English-language pipelines is limited. Behavioral confirmation requires the behavioral battery.
How to fixruntime guardweight-level
Keep the affected token strings out of the model's input — the scan-derived runtime guard carries this model's exact blocklist.
- Fetch this model's guard artifact (`/api/v1/guard/<owner>/<model>`): the confirmed corrupting tokens and the low-norm candidate list, derived from the published scan.
- Screen inbound text with it (the `@ingotai/guard` package is a reference implementation) and route flagged records to a different model or human review — verbatim-copy tasks on flagged strings are the failure mode.
- The underlying cause is undertrained embeddings in the weights; a true fix is weight-level (continued pretraining on the affected tokens) — that is not a patch, it's a training job.
medium Weights inconsistent with claimed parent nvidia/ChronoEdit-14B-Diffusers
This model declares nvidia/ChronoEdit-14B-Diffusers as its base (relation: unspecified), but its token-embedding geometry is incompatible: 4096-dim embeddings vs the parent's 1152-dim. A finetune cannot change embedding width — the lineage label is wrong or misleading. Treat provenance claims on this repo (training data, safety posture, licensing) as unverified.
How to fix
Fix or verify the `base_model` declaration so lineage checks can run.
- If you own the repo: correct the `base_model` field in the model card metadata to the real, public parent.
- If you don't: identify the true parent (config architecture + weight shapes narrow it fast) and re-scan with that lineage in mind.
Remediation guidance addresses the documented findings only. It is evidence-driven repair, not a safety certification of the model.
Check every checkpoint before it ships
Use the web app, API, CLI, or CI gate to scan candidate checkpoints and catch model drift before deployment. Public-model scans publish to the open database; paid plans add the volume needed for continuous checks.
Fingerprint
The durable profile of this model: measured weights-and-metadata facts, rebuilt on every scan and battery run. Updated 2026-08-20.
| vocabulary | 256,384 tokens |
| license | apache-2.0 |
| serialization | safetensors |
| chat template | none |
| claimed lineage | nvidia/ChronoEdit-14B-Diffusers, Wan-AI/Wan2.2-Animate-14B, alibaba-pai/Wan2.2-Fun-A14B-Control-Camera, alibaba-pai/Wan2.2-Fun-A14B-Control, alibaba-pai/Wan2.2-Fun-5B-Control, alibaba-pai/Wan2.2-Fun-5B-InP, alibaba-pai/Wan2.2-Fun-A14B-InP, alibaba-pai/Wan2.2-VACE-Fun-A14B, Wan-AI/Wan2.2-I2V-A14B, Wan-AI/Wan2.2-S2V-14B, Wan-AI/Wan2.2-T2V-A14B, Wan-AI/Wan2.2-TI2V-5B, lightx2v/Wan2.2-Distill-Loras |
| lineage verified | inconsistent vs nvidia/ChronoEdit-14B-Diffusers |
| glitch-token surface | 487 undertrained candidates, 0 plain-ASCII |
Full measured fingerprint
| library | diffusion-single-file |
| pipeline | image-to-video |
| repo files | 45 |
| revision | c4f60d30c55a |
| HF snapshot | 4.9M downloads · 842 likes · updated 2026-08-17 · captured 2026-08-20 |
| embedding tensor | shared.weight · F16 · 256,384×4096 |
| embedding norms | median 624.43 · mean 618.5299 |
| lineage check | inconsistent — cosine undefined over undefined sampled rows vs nvidia/ChronoEdit-14B-Diffusers |
Battery runs (3)the run trace behind the findings — what each job measured
| battery | status | queued | duration | attempts |
|---|---|---|---|---|
| weights | complete | 2026-08-20 18:02 | 4m | 1 |
| weights | complete | 2026-08-20 08:10 | 3m | 1 |
| weights | complete | 2026-08-20 06:35 | 4m | 1 |
Verdict badge
Ship the verdict in your README — it always shows the latest published analysis:
[](https://ingot.tools/models/Comfy-Org/Wan_2.2_ComfyUI_Repackaged)