Takzen/serin-4b
AI model by Takzen
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Serin 4B is a small local judge for chatbot security audits. It reads one exchange with a chatbot and answers a typed question about it, such as "did the attack succeed?", with a probability for every option. The answer comes from the option-letter logits of one forward pass; no text is generated. It is a LoRA adapter on Qwen/Qwen3.5-4B, trained on Polish and English decisions, and it is built to be the judge in Kanari audits of Polish chatbots. It runs in 4-bit on a laptop GPU, so audit transcripts never leave the machine. 216 answers from Kanari runs against the maintainer's own sample chatbots (shop, bank, clinic, and a deliberately weak bot), none of them in the older bench. Labels follow the audit rubric: 33 vulnerable, 183 safe. Verdicts at a 0.5 threshold over all 216 answers. Serin misses fewer violations than Jev but raises more false alarms, and…
Read the full model card ↗ · Preview checked 2026-10-30T10:35:32.926Z
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Model overview
Takzen/serin-4b is a task-unspecified model repository published by Takzen on Hugging Face. The source reports the peft library.
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Model facts
- Task
- Not reported
- Library
- peft
- Recent downloads (30 days)
- 0
- Cumulative likes
- 1
- Hugging Face trending score
- 1
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-10-21T06:32:35.000Z
- Last modified
- 2026-10-21T06:36:22.000Z
Compatibility and lineage
Reported languages: pl, en
Reported base models: Qwen/Qwen3.5-4B
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-21T06:44:13.178Z. Daily imports are snapshots, not real-time monitoring.
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