HopitAI/hopper-g

Hopper (G)

A general-purpose version of Hopper: a LoRA adapter for Qwen3.5-4B that answers typed decision questions in one forward pass by reading the probability of each option letter, with a per-kind calibration map. Served with the Hopper code at https://github.com/hopit-ai/hopper (tag g-1.2.0).

Research and demo use only. This adapter continues training from Hopper 1.0's adapter, whose training data included passages from RACE (non-commercial research only), and its training data also includes material made with LLM-based generation. Do not use it commercially.

What it is

• Base: Qwen/Qwen3.5-4B (revision 851bf6e), LoRA rank 16, alpha 32, the same 12 modules as Hopper.
• Training: continued from Hopper 1.0's adapter on Hopper's decision tasks (at maintenance doses), general-purpose sources (tabular record joins, CLINC150 intents, GSM8K arithmetic) and replay of public training data, with a fixed retention constraint against Hopper 1.0 on a held-out replay bank.
• Serving: identical to Hopper 1.1.1, including the calibration map and the long-menu shortlist (more than 26 options answered in two disclosed stages).

Evaluation (our runs)

On our local run of the Decision Index 0.2 suite (40 benchmarks, A10G, same serving code, only the adapter differing):

	Hopper 1.1.1	Hopper (G) 1.2
balanced raw	52.74	53.50
balanced skill	37.10	38.07
GSM8K	0.318	0.480

Paired bootstrap of the balanced-raw difference: +0.76 (95 % interval +0.55 to +0.98). Seed 1 (trained independently) confirms: balanced raw 53.44 vs 52.74 (+0.70), with every Index area at or above Hopper 1.1.1. Not official scores. Hopper (G) is not tuned for JevBench; we make no claim there.

Limitations

• English, 4B parameters; it reads options, it does not generate reasoning.
• Calibration uses Hopper 1.1.1's map, fitted for Hopper 1.0's adapter; it has not been refitted for these weights.
• Research and demo use only (see above).