AXERA-TECH/Qwen2.5-1.5B-Instruct warn
Weights only ship in a format that can run code when loaded; loading it runs custom code from the repo; its license differs from its base model's. Plus 1 more issue.
claims base: Qwen/Qwen2.5-1.5B-Instruct-GPTQ-INT8, Qwen/Qwen2.5-1.5B-Instruct-GPTQ-INT4 · chat template: not found · view on Hugging Face ↗
Scan coverageStatic battery2026-08-26Weights battery2026-08-26Behavioral batterynot rundetails
| Battery | Looks at | Status |
|---|---|---|
| Static battery | Metadata & packaging | complete 2026-08-26 |
| Weights battery | Weights forensics: no GPU, no download | complete 2026-08-26no token vocabulary — pickle audit only · pickle audit clean |
| Behavioral battery | Live-inference differentials | not run |
Ingot runs three batteries against a model. What each one checks →
Findings
Scanned 2026-08-26 · published from a community scan.
medium Pickle-serialized weights, no safetensors
Weights ship only as pickle-based files (qwen2.5-1.5b-ctx-ax650/model.embed_tokens.weight.bfloat16.bin, qwen2.5-1.5b-ctx-int4-ax650/model.embed_tokens.weight.bfloat16.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.
- Do not load the pickle files in-process — pickle deserialization executes arbitrary code from the file.
- 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.
- Pin the exact revision hash you converted from, and load only your converted safetensors artifact from then on.
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 License differs from claimed parent (mit vs apache-2.0)
This model declares mit while its claimed base Qwen/Qwen2.5-1.5B-Instruct-GPTQ-INT8 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 Chat template dropped vs parent
Qwen/Qwen2.5-1.5B-Instruct-GPTQ-INT8 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.
info Pickle static analysis clean
Opcode-level parse of qwen2.5-1.5b-ctx-ax650/model.embed_tokens.weight.bfloat16.bin, qwen2.5-1.5b-ctx-int4-ax650/model.embed_tokens.weight.bfloat16.bin (no code executed) found only standard serialization globals (0 distinct, all torch/collections/numpy). Pickle remains an executable format — this verifies the current bytes, not future uploads; prefer a safetensors release.
low Pickle checkpoint only partially analyzable
Static analysis could not fully parse: qwen2.5-1.5b-ctx-ax650/model.embed_tokens.weight.bfloat16.bin: legacy parse stopped after 0 pickle(s): unsupported pickle opcode 0xce at 0, qwen2.5-1.5b-ctx-int4-ax650/model.embed_tokens.weight.bfloat16.bin: legacy parse stopped after 0 pickle(s): unsupported pickle opcode 0xce at 0. Unparsed content is unverified.
Check every checkpoint before it ships
Use the web app, API, CLI, or CI gate to scan candidate checkpoints and catch model drift before deployment. Public-model scans publish to the open database; paid plans add the volume needed for continuous checks.
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 AXERA-TECH/Qwen2.5-1.5B-Instruct
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 2026-08-26.
| license | mit |
| serialization | no safetensors pickle custom code |
| chat template | none |
| claimed lineage | Qwen/Qwen2.5-1.5B-Instruct-GPTQ-INT8, Qwen/Qwen2.5-1.5B-Instruct-GPTQ-INT4 |
| lineage verified | unverified — weights battery pending |
Full measured fingerprint
| library | transformers |
| pipeline | text-generation |
| repo files | 86 — pickle: qwen2.5-1.5b-ctx-ax650/model.embed_tokens.weight.bfloat16.bin, qwen2.5-1.5b-ctx-int4-ax650/model.embed_tokens.weight.bfloat16.bin |
| revision | eaa03390b75f |
| HF snapshot | 55 downloads · 1 likes · updated 2025-11-27 · captured 2026-08-25 |
| weights battery | token-embedding scan n/a — no token-embedding tensor found in the pickle checkpoint(s) — pickle checkpoint(s) statically analyzed anyway |
| pickle audit | qwen2.5-1.5b-ctx-ax650/model.embed_tokens.weight.bfloat16.bin, qwen2.5-1.5b-ctx-int4-ax650/model.embed_tokens.weight.bfloat16.bin — 0 standard global(s) · legacy (pre-1.6) format, head-scan only |
Battery runs (1)the run trace behind the findings — what each job measured
| battery | status | queued | duration | attempts |
|---|---|---|---|---|
| weights | complete | 2026-08-25 21:58 | 3s | 1 |
weights run 2026-08-25 — measurements
| probes run | pickle-static-analysis |
Verdict badge
Ship the verdict in your README — it always shows the latest published analysis:
[](https://ingot.tools/models/AXERA-TECH/Qwen2.5-1.5B-Instruct)