Model page

teknium/OpenHermes-2-Mistral-7B warn

Weights only ship in a format that can run code when loaded; its tokenizer differs from its claimed base model.

Could not load this model from the Hugging Face API (private, gated, or nonexistent). Findings below are from our archive.

Scan coverageStatic battery2026-08-25Weights batteryfailedBehavioral batterynot rundetails
BatteryLooks atStatus
Static batteryMetadata & packagingcomplete 2026-08-25
Weights batteryWeights forensics — no GPU, no downloadfailed429 Too Many Requests for https://huggingface.co/api/models/teknium/OpenHermes-2-Mistral-7B
Behavioral batteryLive-inference differentialsnot run

Ingot runs three batteries against a model. What each one checks →

Findings

Scanned 2026-08-25 · published from a community scan.

medium Pickle-serialized weights, no safetensors

Weights ship only as pickle-based files (pytorch_model-00001-of-00002.bin, pytorch_model-00002-of-00002.bin). Loading pickle executes arbitrary code from the file — prefer a safetensors release or load in a sandbox.

How to fix

Convert the weights to safetensors before loading them anywhere that matters.

  1. Do not load the pickle files in-process — pickle deserialization executes arbitrary code from the file.
  2. Convert locally in a sandbox: `pip install safetensors` and use `safetensors.torch.save_file` on a state dict loaded with `torch.load(..., weights_only=True)` (refuses most code-execution payloads), or use Hugging Face's `convert.py` space/script.
  3. Pin the exact revision hash you converted from, and load only your converted safetensors artifact from then on.

medium Vocabulary size differs from claimed parent (32002 vs 32000)

A changed vocab means changed tokenization: strings will split differently than on mistralai/Mistral-7B-v0.1, which can shift behavior on identifiers, codes, and non-English text.

How to fixweight-level

Not patchable: the vocab size mirrors the embedding matrix in the weights. Verify the change was intentional.

  1. Do not edit `vocab_size` in config.json to "match the parent" — it must equal the embedding table in the shipped weights or the model won't load.
  2. Diff the tokenizers (`tokenizer.json` / added_tokens) against the parent to see what was added or removed, and test your own identifiers, codes, and non-English text through both.
  3. If the drift is unexplained by the model card, treat tokenization-sensitive behavior as unvalidated on this model.

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.

architecturemistral · 32 layers · 4096-dim
vocabulary32,002 tokens
licenseapache-2.0
serializationno safetensors pickle
chat templatepresent · sha256:153280e3ff55d19d
claimed lineagemistralai/Mistral-7B-v0.1
lineage verifiedunverified — weights battery pending
Full measured fingerprint
architecturesMistralForCausalLM
librarytransformers
pipelinetext-generation
repo files10 — pickle: pytorch_model-00001-of-00002.bin, pytorch_model-00002-of-00002.bin
revision4c6e34123b14
HF snapshot963 downloads · 255 likes · updated 2023-11-02 · captured 2026-08-25

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