| --- |
| base_model: Qwen/Qwen3.6-35B-A3B |
| library_name: transformers |
| license: apache-2.0 |
| pipeline_tag: text-classification |
| language: |
| - en |
| tags: |
| - qwen3_5_moe |
| - decision-model |
| - typed-decisions |
| - schema-head |
| - jev |
| - calibration |
| - decode-free |
| --- |
| |
| # Standard One 35B SH |
|
|
| **Version:** v1 |
|
|
| **Standard One 35B SH** is Qwen3.6-35B-A3B, a mixture-of-experts model with about 3B active parameters per token, |
| fine-tuned with a **joint schema head** (SH). It reads the scenario once and scores every option of every question in a |
| single forward pass, then returns probabilities through the `POST /v1/systemone` contract used by the other Standard One |
| models. It does not generate text. |
|
|
| | | | |
| |---|---| |
| | Backbone | Qwen3.6-35B-A3B (`qwen3_5_moe`, 40 layers, 256 experts with 8 active per token), fine-tuned for the head and merged; weights in this repository (bfloat16, about 70 GB) | |
| | Head | joint schema head, 68.5M parameters, float32 (`head/`), reading the final layer and layer 29 | |
| | Question types | `choice` (2–255 options), `noul` (yes/no), `score` (ordinal scale) | |
| | Context | trained on requests up to 32,768 tokens | |
| | Prompt format | the Qwen chat template with thinking disabled and no system message (see "Prompt format") | |
| | Smaller models | [StandardOne-8B-SH](https://huggingface.co/StandardThinking/StandardOne-8B-SH) · [StandardOne-3B-SH](https://huggingface.co/StandardThinking/StandardOne-3B-SH) | |
| | License | Apache-2.0 | |
|
|
| ## Why a schema head |
|
|
| A generative decision model reads one answer token per option, so every question in a request needs its own pass and |
| the option count is limited by the label alphabet. The schema head attends over the hidden states of the whole request |
| (the final layer and one intermediate layer), places every question and option in one joint graph, and returns a |
| calibrated distribution for each question at once: |
|
|
| - **Many options.** Intent and routing questions with 100–255 options. |
| - **Many questions per scenario.** All questions of a request share one pass over the scenario. |
| - **Long scenarios.** Decisions buried in long documents. |
|
|
| ## Results |
|
|
| | Benchmark | 3B SH v4 | 8B SH v4 | **35B SH v1 (this release)** | |
| |---|---:|---:|---:| |
| | Decision Index 0.3, public index | 58.08 | 57.40 | **66.26** | |
| | Areas: Knowledge / Language / Retrieval / Tools / Arts | 36.3 / 57.5 / 67.0 / 85.7 / 47.5 | 36.9 / 57.9 / 66.4 / 84.0 / 42.5 | 52.1 / 66.0 / 72.5 / 86.1 / 54.6 | |
| | Decision hidden in a long document (our set, 150 items) | 84.67 | 88.00 | 93.33 | |
| | JevBench public: easy / original / hard (48 / 72 / 111 items) | 100.00 / 95.83 / 63.96 | 100.00 / 94.44 / 75.68 | 100.00 / 97.22 / 78.38 | |
|
|
| Decision Index rows are chance-corrected skill scores (0 = random guessing, 100 = perfect) from our own runs of the public |
| 0.3 suite with the official kit, all 140,178 scoreable requests. The other rows are accuracy in percent, measured with the |
| same engine on identical items. On the JevBench hard tier the model's mean confidence is 80.0 for 78.4 correct (expected |
| calibration error 0.024). |
|
|
| Largest gains over the 8B SH (Decision Index skill points): GSM8K +41.7, BPoMP +35.1, CRUXEval +34.2, PhishNChips +32.4, |
| GPQA Diamond +22.4, iSarcasmEval +21.4, MMLU-Pro +19.7. Intent classification, contracts and API calls stay within |
| 1.3 points of the 8B (CLINC150, BANKING77, ContractNLI, API-Bank); RAGTruth (−2.1) and VAST (−2.2) are slightly lower. |
|
|
| ## Prompt format |
|
|
| Requests are rendered with the included `chat_template.jinja`, thinking disabled (`enable_thinking=False`) and no system |
| message. The reference server in `code/` does this by default. Do not add a system prompt or enable thinking: the head |
| was trained without them, and either changes the hidden states it reads. |
|
|
| ## Quick start |
|
|
| ```bash |
| python -m pip install --upgrade huggingface_hub |
| hf download StandardThinking/StandardOne-35B-SH --local-dir StandardOne-35B-SH |
| python -m pip install -r StandardOne-35B-SH/code/requirements.txt |
| |
| python StandardOne-35B-SH/code/serve_head.py \ |
| --snapshot StandardOne-35B-SH --head StandardOne-35B-SH/head --port 30171 |
| ``` |
|
|
| ```bash |
| curl -s localhost:30171/v1/systemone -H 'content-type: application/json' -d '{ |
| "state": {"message": "Please close my card, I lost it yesterday."}, |
| "questions": { |
| "intent": {"type": "choice", "instructions": "What does the customer want?", |
| "criteria": {"cancel": "close the card", "limit": "change the limit", "other": null}}, |
| "urgent": {"type": "noul", "instructions": "The request is urgent."}, |
| "mood": {"type": "score", "instructions": "How upset is the customer?", "criteria": ["calm", "annoyed", "angry"]} |
| } |
| }' |
| ``` |
|
|
| The reference server is plain PyTorch: backbone in bfloat16, head in float32, one GPU with at least 96 GB of memory. It |
| batches concurrent requests (`--max-batch-requests`, `--max-batch-tokens`) and binds `127.0.0.1` by default. |
|
|
| ## Limitations |
|
|
| - Decision Index numbers are self-scored with the official kit, not a leaderboard entry. |
| - Evaluated on text requests; image inputs are not covered by these results. |
| - Requests longer than 32,768 tokens are outside the trained range. |
|
|
| ## License |
|
|
| Apache-2.0 (weights and head). The base model Qwen3.6-35B-A3B is Apache-2.0. |
|
|
