OpenGVLab/InternVL2-1B warn
claims base: OpenGVLab/InternViT-300M-448px, Qwen/Qwen2-0.5B-Instruct · chat template: present · 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 2026-08-22 |
| Weights battery | Weights forensics — no GPU, no download | complete 2026-08-22151,655-token embedding scanned · 0 undertrained |
| Behavioral battery | Live-inference differentials | not run |
Findings
Scanned 2026-08-22 · 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.
info Embedding-norm glitch scan clean
No undertrained tokens found: every non-special token's embedding norm is above 0.3× the vocabulary median (0.456). The glitch-token data-corruption class has no candidate surface in 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 2026-08-22.
| architecture | internvl_chat |
| parameters | 938.2M |
| vocabulary | 151,655 tokens |
| license | mit |
| serialization | safetensors custom code |
| chat template | present · sha256:793202280c0910ab |
| claimed lineage | OpenGVLab/InternViT-300M-448px, Qwen/Qwen2-0.5B-Instruct |
| lineage verified | unverified — weights battery pending |
| glitch-token surface | clean no undertrained tokens |
Full measured fingerprint
| architectures | InternVLChatModel |
| library | transformers |
| pipeline | image-text-to-text |
| repo files | 19 |
| revision | 0d75ccd166b1 |
| HF snapshot | 777.4k downloads · 82 likes · updated 2025-03-25 · captured 2026-08-21 |
| embedding tensor | language_model.model.embed_tokens.weight · BF16 · 151,655×896 |
| embedding norms | median 0.4561 · mean 0.4556 |
| lineage check | parent weights unreadable (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 07:43 | 17s | 1 |
weights run 2026-08-21 — measurements
| probes run | glitch-norm-scan, lineage-norm-correlation |
| probes skipped | token-decode: no tokenizer.json |
| embedding tensor | language_model.model.embed_tokens.weight · BF16 · 151,655×896 |
| glitch surface | 0 undertrained, 0 plain-ASCII |
| lineage check | not checked (parent weights unreadable (no token-embedding tensor in the safetensors headers — not a text-token model (vision/audio/diffusion checkpoints have no vocabulary to scan))) |
Verdict badge
Ship the verdict in your README — it always shows the latest published analysis:
[](https://ingot.tools/models/OpenGVLab/InternVL2-1B)