HuggingFaceH4/zephyr-7b-beta warn
Its license differs from its base model's; glitch tokens that can silently corrupt ordinary input. Plus 1 minor note.
claims base: mistralai/Mistral-7B-v0.1 · chat template: present · view on Hugging Face ↗
Scan coverageStatic battery2026-08-25Weights battery2026-08-25Behavioral batterynot rundetails
| Battery | Looks at | Status |
|---|---|---|
| Static battery | Metadata & packaging | complete 2026-08-25 |
| Weights battery | Weights forensics — no GPU, no download | complete 2026-08-2532,000-token embedding scanned · 194 undertrained · lineage consistent |
| Behavioral battery | Live-inference differentials | not run |
Ingot runs three batteries against a model. What each one checks →
Findings
Scanned 2026-08-25 · published from a community scan.
low Padding token is the EOS token
The pad token and the (only) EOS token are the same. Fine-tuning frameworks mask pad positions out of the loss, so training on this checkpoint teaches the model to never emit EOS — the Phi-4 / Qwen 2.5 / DeepSeek R1 infinite-generation bug. Safe to serve, hazardous to fine-tune; repoint pad_token at a dedicated token first.
How to fixingot patch
Align the stop-token declarations — a pure metadata fix to `generation_config.json` (and `config.json`).
- Identify the token the chat template actually ends assistant turns with (e.g. `<|eot_id|>`, `<end_of_turn>`, `<|im_end|>`) and make sure its id is in `generation_config.json`'s `eos_token_id` list.
- Keep `config.json`'s `eos_token_id` consistent with (or a subset of) `generation_config.json`'s — runtimes differ in which file they read.
- For the pad-equals-EOS hazard: repoint `pad_token` at a dedicated padding token before fine-tuning; serving is unaffected.
- Until the repo is fixed, pass explicit stop tokens to your serving stack (e.g. vLLM `stop_token_ids`, llama.cpp `--override-kv tokenizer.ggml.eos_token_id`).
medium License differs from claimed parent (mit vs apache-2.0)
This model declares mit while its claimed base mistralai/Mistral-7B-v0.1 declares apache-2.0. 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 194 undertrained tokens (norm < 0.3× the vocabulary median of 0.180), including 10 plain-ASCII strings that can appear in ordinary input as identifiers — e.g. "<0xFB>", "<0xFD>", "<0xFF>", "<0xFA>", "<0xFC>", "<0xFE>", "iNdEx", "febbra". 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 mistralai/Mistral-7B-v0.1
Mean cosine similarity of 64 sampled token-embedding rows against mistralai/Mistral-7B-v0.1 is 0.998 — 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.
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 HuggingFaceH4/zephyr-7b-beta
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 2026-08-25.
| architecture | mistral · 32 layers · 4096-dim |
| parameters | 7241.7M |
| vocabulary | 32,000 tokens |
| license | mit |
| serialization | safetensors pickle |
| chat template | present · sha256:66291cf0045c2425 |
| claimed lineage | mistralai/Mistral-7B-v0.1 |
| lineage verified | consistent vs mistralai/Mistral-7B-v0.1 — embedding-row cosine 0.998 |
| glitch-token surface | 194 undertrained candidates, 10 plain-ASCII |
Full measured fingerprint
| architectures | MistralForCausalLM |
| library | transformers |
| pipeline | text-generation |
| repo files | 31 — pickle: pytorch_model-00001-of-00008.bin, pytorch_model-00002-of-00008.bin, pytorch_model-00003-of-00008.bin, pytorch_model-00004-of-00008.bin, pytorch_model-00005-of-00008.bin, pytorch_model-00006-of-00008.bin, pytorch_model-00007-of-00008.bin, pytorch_model-00008-of-00008.bin |
| revision | 892b3d7a7b1c |
| HF snapshot | 106.0k downloads · 1.9k likes · updated 2024-10-16 · captured 2026-08-25 |
| embedding tensor | model.embed_tokens.weight · BF16 · 32,000×4096 |
| embedding norms | median 0.1797 · mean 0.1768 |
| lineage check | consistent — cosine 0.9977 over 64 sampled rows vs mistralai/Mistral-7B-v0.1 |
| glitch-token samples | "<0xFB>", "<0xFD>", "<0xFF>", "<0xFA>", "<0xFC>", "<0xFE>", "iNdEx", "febbra", "NdEx", "uitgen" |
Battery runs (1)the run trace behind the findings — what each job measured
| battery | status | queued | duration | attempts |
|---|---|---|---|---|
| weights | complete | 2026-08-25 20:26 | 34s | 1 |
weights run 2026-08-25 — measurements
| probes run | glitch-norm-scan, zero-template-token-scan, lineage-norm-correlation |
| embedding tensor | model.embed_tokens.weight · BF16 · 32,000×4096 |
| glitch surface | 194 undertrained, 10 plain-ASCII |
| lineage check | consistent — cosine 0.9977 over 64 rows vs mistralai/Mistral-7B-v0.1 |
Verdict badge
Ship the verdict in your README — it always shows the latest published analysis:
[](https://ingot.tools/models/HuggingFaceH4/zephyr-7b-beta)