unsloth/DeepSeek-R1-Distill-Qwen-7B-bnb-4bit warn
Its license differs from its base model's; glitch tokens that can silently corrupt ordinary input.
Could not load this model from the Hugging Face API (private, gated, or nonexistent). Findings below are from our archive.
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 2026-08-21152,064-token embedding scanned · 14086 undertrained · lineage consistent |
| 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 License differs from claimed parent (apache-2.0 vs mit)
This model declares apache-2.0 while its claimed base deepseek-ai/DeepSeek-R1-Distill-Qwen-7B declares mit. 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 Undertrained (glitch) token surface in vocabulary
Embedding-norm scan flagged 14086 undertrained tokens (norm < 0.3× the vocabulary median of 1.160), including 3462 plain-ASCII strings that can appear in ordinary input as identifiers — e.g. "TokenNameIdentifier", "ForCanBeConverted", "ForCanBeConvertedToF", "$PostalCodesNL", "<unk>", "useRalative", "useRal", "Cumhurba". In models where this class was tested behaviorally, such tokens silently rewrote user input into confident, schema-valid, wrong output. These are candidates from the weights alone; 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.
info Weights consistent with claimed parent deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
Mean cosine similarity of 64 sampled token-embedding rows against deepseek-ai/DeepSeek-R1-Distill-Qwen-7B is 1.000 — the weights plausibly descend from the declared base (relation: unspecified).
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.
Fingerprint
The durable profile of this model: measured weights-and-metadata facts, rebuilt on every scan and battery run. Updated 2026-08-21.
| architecture | qwen2 · 28 layers · 3584-dim |
| parameters | 7820.1M |
| vocabulary | 152,064 tokens |
| license | apache-2.0 |
| serialization | safetensors |
| chat template | present · sha256:56a1447ad31926fd |
| claimed lineage | deepseek-ai/DeepSeek-R1-Distill-Qwen-7B |
| lineage verified | consistent vs deepseek-ai/DeepSeek-R1-Distill-Qwen-7B — embedding-row cosine 1.000 |
| glitch-token surface | 14,086 undertrained candidates, 3,462 plain-ASCII |
Full measured fingerprint
| architectures | Qwen2ForCausalLM |
| library | transformers |
| pipeline | text-generation |
| repo files | 8 |
| revision | 5c46879548e7 |
| HF snapshot | 5.1k downloads · 3 likes · updated 2025-02-14 · captured 2026-08-21 |
| embedding tensor | model.embed_tokens.weight · BF16 · 152,064×3584 |
| embedding norms | median 1.1598 · mean 1.0362 |
| lineage check | consistent — cosine 1 over 64 sampled rows vs deepseek-ai/DeepSeek-R1-Distill-Qwen-7B |
| glitch-token samples | "TokenNameIdentifier", "ForCanBeConverted", "ForCanBeConvertedToF", "$PostalCodesNL", "<unk>", "useRalative", "useRal", "Cumhurba", "webElementX", "NdrFc", "_ComCallableWrapper", "NdrFcShort" |
Battery runs (1)the run trace behind the findings — what each job measured
| battery | status | queued | duration | attempts |
|---|---|---|---|---|
| weights | complete | 2026-08-21 05:11 | 78s | 1 |
weights run 2026-08-21 — measurements
| probes run | glitch-norm-scan, lineage-norm-correlation |
| embedding tensor | model.embed_tokens.weight · BF16 · 152,064×3584 |
| glitch surface | 14,086 undertrained, 3,462 plain-ASCII |
| lineage check | consistent — cosine 1 over 64 rows vs deepseek-ai/DeepSeek-R1-Distill-Qwen-7B |
Verdict badge
Ship the verdict in your README — it always shows the latest published analysis:
[](https://ingot.tools/models/unsloth/DeepSeek-R1-Distill-Qwen-7B-bnb-4bit)