Raiff1982/codette-lora-adapters warn
claims base: meta-llama/Llama-3.1-8B-Instruct · chat template: not found · view on Hugging Face ↗
Scan coverage
Ingot runs three batteries against a model. What each one checks →
| Battery | Looks at | Status |
|---|---|---|
| Static battery | Metadata & packaging | complete 2026-08-21 |
| Weights battery | Weights forensics — no GPU, no download | n/ano token-embedding tensor in the safetensors headers — not a text-token model (vision/audio/diffusion checkpoints have no vocabulary to scan) |
| Behavioral battery | Live-inference differentials | not run |
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
meta-llama/Llama-3.1-8B-Instruct 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.
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.
| license | llama3.1 |
| serialization | safetensors + gguf pickle custom code |
| chat template | none |
| claimed lineage | meta-llama/Llama-3.1-8B-Instruct |
| lineage verified | unverified — weights battery pending |
Full measured fingerprint
| library | peft |
| pipeline | text-generation |
| repo files | 738 — pickle: behavioral/consciousness/checkpoint-115/optimizer.pt, behavioral/consciousness/checkpoint-115/rng_state.pth, behavioral/consciousness/checkpoint-115/scheduler.pt, behavioral/consciousness/checkpoint-115/training_args.bin, behavioral/constraint_tracker/checkpoint-24/optimizer.pt, behavioral/constraint_tracker/checkpoint-24/rng_state.pth, behavioral/constraint_tracker/checkpoint-24/scheduler.pt, behavioral/constraint_tracker/checkpoint-24/training_args.bin, behavioral/davinci/checkpoint-110/optimizer.pt, behavioral/davinci/checkpoint-110/rng_state.pth |
| revision | 5794694fe147 |
| HF snapshot | 262 downloads · 0 likes · updated 2026-07-08 · captured 2026-08-21 |
| weights battery | token-embedding scan n/a — no token-embedding tensor in the safetensors headers — not a text-token model (vision/audio/diffusion checkpoints have no vocabulary to scan) |
Battery runs
The run trace behind the findings above: every deep-battery job for this model, with what each run measured or why it failed. Findings are only as good as the runs that produced them.
| battery | status | queued | duration | attempts |
|---|---|---|---|---|
| weights | complete | 2026-08-21 05:16 | 2m | 1 |
weights run 2026-08-21 — measurements
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 Raiff1982/codette-lora-adapters
Remediation guidance addresses the documented findings only. It is evidence-driven repair, not a safety certification of the model.
Verdict badge
Ship the verdict in your README — it always shows the latest published analysis:
[](https://ingot.tools/models/Raiff1982/codette-lora-adapters)