Instructions to use yunqu/mentat-sys1-v0.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use yunqu/mentat-sys1-v0.3 with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
mentat-sys1-v0.3
Decisions with probabilities.
A 4B model for choosing actions, using tools and making structured decisions. Give it a state and typed questions; it returns answer probabilities in one forward pass per question, without generating answer text.
Qwen3.5-4B · Text / JSON · 16K context · LoRA adapter + decision readout
GitHub · Code & accelerated inference · Team · THU-IDM · Demos · Quick start · Results · Documentation
See it in action
Recorded games and completed workflows. Click a demo to watch the enlarged replay.
The model receives structured text/JSON states and selects actions.
Controllers provide Mario lookahead, Doom aiming/navigation, football physics/off-ball AI, and chess legal/tactical facts. Shopping and Workspace use local mock sites. Game clips show selected highlights.
Results
| Measurement | mentat-sys1-v0.3 | Jev, reported |
|---|---|---|
| Intern-Decision — average accuracy (%) ↑ | 89.59% | 88.74% |
| JevBench — correct answers (public set) ↑ | 204/231 | 199/231 |
| Typed Decisions — Brier score ↓ | 0.05403 | 0.148 |
| Decision Index 0.2.1 ↑ | 52.07* | 57.91 |
| Latency (ms) ↓ | 21.47 ms | 150 ms† |
Jev benchmark results: StartLux results.
* DI: 149,816 requests, 37 tasks; HLE unmeasured (zero contribution, original weights); abstentions count as wrong.
† mentat: one question, accelerated runtime, warm A800, 600 localhost HTTP requests. Jev: TypeSafe’s official 150 ms reference, question count unspecified.
Quick start
Python 3.12 and a CUDA GPU:
hf download yunqu/mentat-sys1-v0.3 --revision v0.3 --local-dir mentat-v0.3
hf download Qwen/Qwen3.5-4B \
--revision 851bf6e806efd8d0a36b00ddf55e13ccb7b8cd0a \
--local-dir qwen-base
pip install -r mentat-v0.3/requirements.txt
python mentat-v0.3/infer.py --base-model qwen-base --input mentat-v0.3/example.json
Supports named choices (choice), yes/no (noul) and ordered scores (score). Request / response example and HTTP API.
License
Adapter and bundled code: Apache-2.0. The separately downloaded Qwen base retains its upstream license. NOTICE.
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