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README.md
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and it tells you how likely each option is, in one forward pass with no generated tokens. Routing a ticket, spotting a phishing mail,
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picking the next action for a robot: same call, same model.
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## TL;DR
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- **Quality.** Mean accuracy 0.801 across 17 public suites (Seb-9B 0.793, hosted Jev 1.13 0.786, Laya 0.694). Biggest gains over v1:
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and it tells you how likely each option is, in one forward pass with no generated tokens. Routing a ticket, spotting a phishing mail,
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picking the next action for a robot: same call, same model.
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**Read the post:** [Seb-9B-v2: a small model for the decisions your app makes all day](https://huggingface.co/ironbcc/Seb-9B-v2/blob/main/blog/post.md) (edge use, first-tier LLM router, robots, numbers).
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## TL;DR
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- **Quality.** Mean accuracy 0.801 across 17 public suites (Seb-9B 0.793, hosted Jev 1.13 0.786, Laya 0.694). Biggest gains over v1:
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