inference-optimization/Qwen3-8B-speculators.peagle-qwen3arch-ckpt4 warn
Loading it runs custom code from the repo; the chat template was dropped from its base model, which changes behavior. Plus 2 minor notes.
claims base: Qwen/Qwen3-8B · chat template: not found · view on Hugging Face ↗
Scan coverageStatic battery2026-08-21Weights battery2026-08-21Behavioral batterynot rundetails
| Battery | Looks at | Status |
|---|---|---|
| Static battery | Metadata & packaging | complete 2026-08-21 |
| Weights battery | Weights forensics — no GPU, no download | complete 2026-08-21151,936-token embedding scanned · 8384 undertrained · lineage inconclusive |
| Behavioral battery | Live-inference differentials | not run |
Ingot runs three batteries against a model. What each one checks →
Findings
Scanned 2026-08-21 · published from a community scan.
medium Repo ships executable Python (trust_remote_code)
The repository contains custom code files that run in-process when loaded with trust_remote_code=True. Pin the revision hash and review the code before loading.
How to fix
Review and pin the custom code; never float on `main` with trust_remote_code=True.
- Read every `.py` file in the repo before first load — this code runs in your process.
- Pin the revision: `from_pretrained(model_id, revision="<commit sha>", trust_remote_code=True)` so a later push can't swap the code under you.
- Prefer a version of the architecture already in `transformers` if one exists, which removes the remote-code requirement entirely.
medium Chat template dropped vs parent
Qwen/Qwen3-8B ships a chat template; this repo does not. Serving stacks will silently fall back to a generic template, changing behavior. (In our 296-model census, 78% of pure quantization re-releases changed or dropped the template.)
How to fixingot patch
Restore the parent's chat template in `tokenizer_config.json` — a pure metadata fix.
- Run `ingot patch <owner/model>` — the patch manifest carries the parent's template and applies it to a local copy's `tokenizer_config.json`.
- Or fix by hand: copy the `chat_template` value from the parent repo's `tokenizer_config.json` into this model's, and pin your serving stack to that file.
- If the drift was intentional (the author retrained on a new template), confirm that in the model card before "fixing" it — restoring the parent template on retrained weights changes behavior too.
low Undertrained tokens in vocabulary (non-ASCII tail)
Embedding-norm scan flagged 8384 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.
low Lineage vs claimed parent Qwen/Qwen3-8B inconclusive
Mean embedding-row cosine similarity to the declared base is 0.737 — below the 0.8 typical of true derivatives but not low enough to call mislabeled. Heavy continued pretraining or vocabulary surgery can look like this; verify provenance before relying on the parent's safety or licensing posture.
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.
Fix it
Some findings are metadata-level and patchable — apply the fixes to your local copy (your weights never leave your machine):
npx @ingotai/scan patch inference-optimization/Qwen3-8B-speculators.peagle-qwen3arch-ckpt4
Remediation guidance addresses the documented findings only. It is evidence-driven repair, not a safety certification of the model.
Fingerprint
The durable profile of this model: measured weights-and-metadata facts, rebuilt on every scan and battery run. Updated 2026-08-21.
| parameters | 1600.9M |
| vocabulary | 151,936 tokens |
| license | apache-2.0 |
| serialization | safetensors custom code |
| chat template | none |
| claimed lineage | Qwen/Qwen3-8B |
| lineage verified | inconclusive vs Qwen/Qwen3-8B — embedding-row cosine 0.737 |
| glitch-token surface | 8,384 undertrained candidates, 0 plain-ASCII |
Full measured fingerprint
| architectures | PEagleDraftModel |
| library | speculators |
| repo files | 5 |
| revision | 8132772cc771 |
| HF snapshot | 19.7k downloads · 1 likes · updated 2026-06-16 · captured 2026-08-21 |
| embedding tensor | embed_tokens.weight · BF16 · 151,936×4096 |
| embedding norms | median 2.2282 · mean 1.9769 |
| lineage check | inconclusive — cosine 0.737 over 64 sampled rows vs Qwen/Qwen3-8B |
Battery runs (1)the run trace behind the findings — what each job measured
| battery | status | queued | duration | attempts |
|---|---|---|---|---|
| weights | complete | 2026-08-21 05:10 | 3m | 1 |
weights run 2026-08-21 — measurements
| probes run | glitch-norm-scan, lineage-norm-correlation |
| probes skipped | token-decode: no tokenizer.json |
| embedding tensor | embed_tokens.weight · BF16 · 151,936×4096 |
| glitch surface | 8,384 undertrained, 0 plain-ASCII |
| lineage check | inconclusive — cosine 0.737 over 64 rows vs Qwen/Qwen3-8B |
Verdict badge
Ship the verdict in your README — it always shows the latest published analysis:
[](https://ingot.tools/models/inference-optimization/Qwen3-8B-speculators.peagle-qwen3arch-ckpt4)