WillHeld/DiVA-llama-3-v0-8b warn
Loading it runs custom code from the repo; its license differs from its base model's; the chat template differs from its base model, which changes behavior. Plus 1 more issue.
claims base: meta-llama/Llama-3.1-8B-Instruct · chat template: present · 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 2026-08-2151,866-token embedding scanned · 0 undertrained · lineage inconsistent |
| 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 License differs from claimed parent (mpl-2.0 vs llama3.1)
This model declares mpl-2.0 while its claimed base meta-llama/Llama-3.1-8B-Instruct declares llama3.1. Verify the re-license is permitted before commercial use.
How to fix
Verify the re-license is actually permitted before relying on it.
- Read the parent's license for derivative-work and re-licensing terms — many open-weight licenses (e.g. Llama-family) do not permit arbitrary re-licensing.
- If the re-license is not permitted, the parent's terms govern your use regardless of what this repo declares.
medium Chat template differs from claimed parent
The chat template does not match meta-llama/Llama-3.1-8B-Instruct's. Template drift silently changes model behavior even when weights are identical — 37% of drifted derivatives in our census left it undisclosed. Diff the templates before deploying.
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.
info Embedding-norm glitch scan clean
No undertrained tokens found: every non-special token's embedding norm is above 0.3× the vocabulary median (0.746). The glitch-token data-corruption class has no candidate surface in this model.
medium Weights inconsistent with claimed parent meta-llama/Llama-3.1-8B-Instruct
This model declares meta-llama/Llama-3.1-8B-Instruct as its base (relation: unspecified), but its token-embedding geometry is incompatible: 1280-dim embeddings vs the parent's 4096-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.
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.
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 WillHeld/DiVA-llama-3-v0-8b
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.
| architecture | diva |
| parameters | 2486.9M |
| vocabulary | 128,256 tokens |
| license | mpl-2.0 |
| serialization | safetensors custom code |
| chat template | present · sha256:b48c47f644389271 |
| claimed lineage | meta-llama/Llama-3.1-8B-Instruct |
| lineage verified | inconsistent vs meta-llama/Llama-3.1-8B-Instruct |
| glitch-token surface | clean no undertrained tokens |
Full measured fingerprint
| architectures | DiVAModel |
| library | transformers |
| pipeline | feature-extraction |
| repo files | 14 |
| revision | 6e761b15ebde |
| HF snapshot | 1.1k downloads · 35 likes · updated 2024-12-19 · captured 2026-08-21 |
| embedding tensor | connector.embed_tokens.weight · F32 · 51,866×1280 |
| embedding norms | median 0.7463 · mean 0.7393 |
| lineage check | inconsistent — cosine undefined over undefined sampled rows vs meta-llama/Llama-3.1-8B-Instruct |
Battery runs (1)the run trace behind the findings — what each job measured
| battery | status | queued | duration | attempts |
|---|---|---|---|---|
| weights | complete | 2026-08-21 05:12 | 38s | 1 |
weights run 2026-08-21 — measurements
| probes run | glitch-norm-scan, lineage-norm-correlation |
| embedding tensor | connector.embed_tokens.weight · F32 · 51,866×1280 |
| glitch surface | 0 undertrained, 0 plain-ASCII |
| lineage check | inconsistent — cosine undefined over undefined rows vs meta-llama/Llama-3.1-8B-Instruct |
Verdict badge
Ship the verdict in your README — it always shows the latest published analysis:
[](https://ingot.tools/models/WillHeld/DiVA-llama-3-v0-8b)