Duplicate from ZefanCai/Open-Jev-9B

Co-authored-by: Zefan Cai <ZefanCai@users.noreply.huggingface.co>

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LICENSE

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LICENSE-CODE

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+MIT License
+
+Copyright (c) 2026 Open-Jev contributors
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+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3.5-9B
+base_model_relation: adapter
+library_name: peft
+tags:
+- open-jev
+- qwen3.5
+- lora
+- non-generative
+- typed-decisions
+---
+
+# Open-Jev-9B
+
+**A trained LoRA adapter and scalar decision head for Qwen/Qwen3.5-9B.** This repository contains the completed Open-Jev decision checkpoint, not merged or standalone base-model weights. It requires the exact upstream model/tokenizer revision **`c202236235762e1c871ad0ccb60c8ee5ba337b9a`** and the [Open-Jev loader](https://github.com/Zefan-Cai/Open-Jev).
+
+Open-Jev scores caller-supplied candidates directly and returns typed decisions without autoregressive answer generation:
+
+- **Choice:** probabilities over the supplied candidate set and its most probable candidate.
+- **Noul:** a probability for a yes/no question.
+- **Score:** probabilities over supplied ordinal levels and their expected value.
+
+The adapter targets the Qwen text backbone. A generic `AutoPeftModel` text-generation call does not implement this interface or apply the separate decision head and saved temperature.
+
+## Download and run
+
+Use a suitable GPU with the upstream weights available locally or downloadable from Hugging Face. The loader uses the pinned upstream revision in `package/checkpoint/model.json`.
+
+```bash
+git clone https://github.com/Zefan-Cai/Open-Jev.git
+cd Open-Jev
+python -m pip install -e '.[train]'
+hf download ZefanCai/Open-Jev-9B --local-dir ./checkpoints/open-jev-9b
+python -m jev.server \
+  --checkpoint ./checkpoints/open-jev-9b/package/checkpoint \
+  --device cuda:0 --max-length 4096 --batch-size 1 --no-prefix-cache \
+  --host 127.0.0.1 --port 8791
+```
+
+The repository's `train` extra supplies inference dependencies too, including Transformers 5.10.2 and PEFT 0.19.1. Prefix caching is opt-in and is disabled above; real-checkpoint GPU A/B validation remains separate. For reproducible deployments, add `--revision <commit>` to `hf download` using a commit from this model repository's history.
+
+Once the server is ready, submit a request. This is an input example, not a claim about a recorded prediction:
+
+```bash
+curl http://127.0.0.1:8791/v1/systemone \
+  -H 'Content-Type: application/json' \
+  -d '{"state":"I was charged twice and want a refund.","questions":{"intent":{"type":"choice","instructions":"Choose the customer intent.","criteria":{"billing":"A payment or refund issue","technical":"A malfunction or setup issue","other":"Another request"}}}}'
+```
+
+The server returns declared keys and probabilities. It does not execute the proposed actions. The model's maximum input length is 4,096 tokens per independently scored candidate; input is rejected rather than silently truncated.
+
+## Training and data
+
+- 20,204 optimizer steps with global batch 4: **80,816 consumed training rows**, one full pass over the frozen `release-v2` training split.
+- LoRA rank 8, alpha 16; scalar head initialized from the pretrained Yes-minus-No readout and trained jointly with LoRA.
+- Training source commit: `99e881108c6cacadafd364088505e84975ca43fc`.
+- Frozen data manifest SHA-256: `56105dc9fc89ef74919f5beb60bb6ae8c6e17bb95699dab59205f67d8b338d97`.
+- Saved temperature: `1.8969118766347646`; fitted only on 512 calibration rows.
+
+The [public dataset repository](https://huggingface.co/datasets/ZefanCai/Open-Jev) provides `release-v2-redistributable`. Its training split has **79,116 rows**, excluding the 1,700 original training records from `wikispeedia-v1` because redistribution permission for that archive has not been confirmed. It is **not byte-identical to the 80,816-row training set** used for these weights. The original manifest and split hashes remain recorded in [package/provenance.json](package/provenance.json); no source dataset rows are bundled here.
+
+The later browser/drone expansion and five later extraction-control corpora are not part of this checkpoint's training mixture. Public game videos may use separately identified older pilot checkpoints and are not automatically evidence for these full-pass weights.
+
+## Full held-out evaluation
+
+The existing full-data evaluation covers **10,532 test + 15,920 OOD = 26,452 records**, with zero missing, duplicate, or failed inference records. This evaluation used the original frozen mixture, including its Wiki records, rather than the redistributable projection. Its five inference-file hashes match the weights and metadata published here.
+
+| Split | All rows | Hard correct / hard rows | Hard accuracy | Expected accuracy | NLL | Brier | ECE |
+| --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
+| Test | 10,532 | 9,799 / 10,046 | 97.54% | 94.72% | 0.130947 | 0.039113 | 0.007707 |
+| OOD | 15,920 | 14,205 / 15,446 | 91.97% | 90.40% | 0.299441 | 0.126647 | 0.037398 |
+
+Hard accuracy excludes soft-target rows. Expected accuracy is the reference target mass at the chosen candidate across all rows; it is not a game-win or workflow-completion rate. NLL, Brier, and ECE use all rows and the saved calibration. Full machine-readable results are in [evaluation/full-data.json](evaluation/full-data.json).
+
+No full-data baseline was evaluated, so this table does not establish training gain. The original package also preserves the training run's separate 512-test/512-OOD sampled metrics in [package/metrics.json](package/metrics.json) and its original card in [package/README.md](package/README.md). Those smaller sampled results should not be confused with the full-data table above.
+
+## Artifact layout and verification
+
+`package/` is the unchanged verified inference package, including its original manifest, card, calibration, provenance, and sampled metrics. The root [release-manifest.json](release-manifest.json) binds the complete Hugging Face release layout.
+
+| Artifact | SHA-256 |
+| --- | --- |
+| LoRA adapter | `f85650a8fb97c6d0ac3e948cdca2f30a0ca6ace8b8a43aebca1c152fe38aeb75` |
+| Scalar head | `229fe9800384e824135e59d1af59bda7346da031aea61640be5f456b9be6ce70` |
+| Original package manifest | `e83fd15c8715c9a7e474afd0830d55b0fe4b25ab61910114f6e36437a2964e37` |
+
+The original evaluated checkpoint directory had digest `a691105dd5751bfcf72d276a6ce075d45054db77ae3272e87b5f07b2bd7e2193`. The packaged five-file inference directory has digest `9302c52feba99d079918755f2469f4f088266e9786327bab550248f3d83716d3` because the packaging whitelist omits the generated adapter README. These directory digests are not interchangeable: the evaluation binding is verified **per inference file**.
+
+Release checks cover manifest bytes, pinned model/revision, licenses, calibration, finite CPU adapter/head tensors, and correspondence to the completed evaluation's inference files. No GPU inference was repeated during this upload. The trainer's historical reload logits were checked, but training did not record a contemporaneous output-weight digest; this upload does not invent one.
+
+Synthetic held-out decision metrics do not establish broad real-world reliability, closed-loop browser/game/flight success, or a calibrated probability guarantee outside the evaluated distribution.
+
+## License
+
+The trained adapter and head are released under **Apache-2.0**, with the complete pinned Qwen/Alibaba Cloud attribution in [LICENSE](LICENSE) and [UPSTREAM.md](UPSTREAM.md). Open-Jev source code is **MIT**, preserved in [LICENSE-CODE](LICENSE-CODE). The upstream model/tokenizer must be obtained separately under their own terms.

UPSTREAM.md

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+# Qwen attribution and license
+
+Copyright 2026 Alibaba Cloud.
+
+The accompanying `LICENSE` is the exact Apache License 2.0 text retrieved from
+[Qwen3.5-2B revision 15852e8](https://huggingface.co/Qwen/Qwen3.5-2B/raw/15852e8c16360a2fea060d615a32b45270f8a8fc/LICENSE).
+Its SHA-256 is
+`bbedc3fda3305820b977265f01b8619d87570a6739de3a5582c3464840f1e57a`.
+The same bytes were independently verified for all three selected revisions:
+
+| Upstream model | Fixed revision |
+| --- | --- |
+| Qwen/Qwen3.5-2B | `15852e8c16360a2fea060d615a32b45270f8a8fc` |
+| Qwen/Qwen3.5-9B | `c202236235762e1c871ad0ccb60c8ee5ba337b9a` |
+| Qwen/Qwen3.8-27B | `1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0` |
+
+See [the source audit](https://github.com/Zefan-Cai/Open-Jev-Dev/blob/main/docs/model-provenance.md) for the fixed README,
+license and revision-API evidence. The inspected inventories contain no
+upstream `NOTICE` file; notices in additional bundled artifacts still apply.
+
+Open-Jev modifies the upstream model by training LoRA adapters and a scalar
+decision head, initially derived from the upstream Yes-minus-No embedding
+rows. Its published inference artifacts require the exact corresponding
+upstream weights and the Open-Jev loader. They are not unmodified Qwen models,
+standard text-generation checkpoints, or a reproduction of private Jev weights.
+
+The checkpoint packaging tool applies Apache-2.0 to its inference weight
+package and retains the upstream copyright and terms. Original Open-Jev source
+code remains under the repository MIT license, which is included separately
+when packaging. The generated data's CC0 markers do not license model weights.
+No checkpoint has been published merely by adding this notice or the packaging
+tool; an actual package must name its model revision, training run and measured
+results. No endorsement by Alibaba Cloud, the Qwen Team or TypeSafe is implied.

package/LICENSE

@@ -0,0 +1,202 @@
+
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+      (a) You must give any other recipients of the Work or
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+   Copyright 2026 Alibaba Cloud
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
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+   See the License for the specific language governing permissions and
+   limitations under the License.

package/LICENSE-CODE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 Open-Jev contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

package/README.md

@@ -0,0 +1,58 @@
+---
+license: apache-2.0
+base_model: Qwen/Qwen3.5-9B
+tags:
+- open-jev
+- non-generative
+---
+
+# Open-Jev decision checkpoint
+
+This local package contains an Open-Jev LoRA adapter and scalar decision head derived from Qwen/Qwen3.5-9B.
+Upstream revision: `c202236235762e1c871ad0ccb60c8ee5ba337b9a`. The upstream model/tokenizer are required and are not bundled.
+
+The adapter and Yes-minus-No-initialized scalar head are modified training products. Weights use Apache-2.0; Open-Jev source code remains MIT. See LICENSE, LICENSE-CODE and UPSTREAM.md.
+
+## Recorded training
+
+20,204 optimizer steps × global batch 4 = 80,816 consumed rows; 80,816 selected train rows out of 80,816.
+Dataset: release-v2; source composition: release-v1, reasoning-control-v1.
+Training coverage: one full pass over all train rows.
+Topology: single process with gradient accumulation.
+Code commit: `99e881108c6cacadafd364088505e84975ca43fc`. Full normalized hyperparameters and data hashes are in provenance.json.
+
+## Recorded evaluation
+
+The source run evaluated 512/10,532 test rows and 512/15,920 OOD rows using source/kind-balanced selection.
+These results do not represent a separate full-data evaluation of all 26,452 held-out rows. Other pilot or benchmark results are not merged into this card.
+Temperature 1.8969119 was recorded for 512 calibration rows; their ID hash is retained.
+
+| Measurement | Rows | Hard-label accuracy | Expected accuracy | NLL | Brier | ECE |
+| --- | ---: | ---: | ---: | ---: | ---: | ---: |
+| baseline_calibrated_ood | 512 | 0.667355 | 0.637869 | 0.864411 | 0.427617 | 0.0693149 |
+| baseline_calibrated_test | 512 | 0.646809 | 0.615909 | 0.876303 | 0.43757 | 0.0380326 |
+| baseline_ood | 512 | 0.667355 | 0.637869 | 0.862788 | 0.426134 | 0.0357867 |
+| baseline_test | 512 | 0.646809 | 0.615909 | 0.881718 | 0.441505 | 0.0609296 |
+| calibrated_ood | 512 | 0.923554 | 0.886388 | 0.327474 | 0.112074 | 0.0283001 |
+| calibrated_test | 512 | 0.951064 | 0.903786 | 0.254392 | 0.0741149 | 0.0294664 |
+| trained_ood | 512 | 0.923554 | 0.886388 | 0.413766 | 0.117756 | 0.0485585 |
+| trained_test | 512 | 0.951064 | 0.903786 | 0.273097 | 0.0792583 | 0.0344311 |
+
+## Load with Open-Jev
+
+From an Open-Jev source checkout, install the training/inference dependencies and start the decision server:
+
+```bash
+python -m pip install '.[train]'
+python -m jev.server --checkpoint /path/to/package/checkpoint \
+  --device cuda:0 --max-length 4096 --batch-size 1 \
+  --host 127.0.0.1 --port 8791
+```
+
+A suitable GPU and the exact upstream weights/tokenizer revision listed above are required, either cached locally or downloaded by the loader. The scalar decision head requires Open-Jev's loader; AutoPeftModel generation alone does not implement these decisions.
+
+## Verification scope
+
+Packaging verified source hashes, completed-step logs, frozen-data selection, model identity, calibration binding and saved reload logits. Both temperatures and all eight core/grouped metric sections were recomputed from the verified saved predictions using the repository's stdlib metrics. It hashes the current weight bytes but does not load tensors or repeat model inference. The training summary did not record output-weight hashes, so the historical reload is not an independent verification of the current packaged bytes.
+
+Synthetic sampled scores do not establish general agent, browser, game, flight or closed-loop competence. The manifest identifies a local package; it does not imply an upload or public release.

package/UPSTREAM.md

@@ -0,0 +1,33 @@
+# Qwen attribution and license
+
+Copyright 2026 Alibaba Cloud.
+
+The accompanying `LICENSE` is the exact Apache License 2.0 text retrieved from
+[Qwen3.5-2B revision 15852e8](https://huggingface.co/Qwen/Qwen3.5-2B/raw/15852e8c16360a2fea060d615a32b45270f8a8fc/LICENSE).
+Its SHA-256 is
+`bbedc3fda3305820b977265f01b8619d87570a6739de3a5582c3464840f1e57a`.
+The same bytes were independently verified for all three selected revisions:
+
+| Upstream model | Fixed revision |
+| --- | --- |
+| Qwen/Qwen3.5-2B | `15852e8c16360a2fea060d615a32b45270f8a8fc` |
+| Qwen/Qwen3.5-9B | `c202236235762e1c871ad0ccb60c8ee5ba337b9a` |
+| Qwen/Qwen3.8-27B | `1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0` |
+
+See [the source audit](https://github.com/Zefan-Cai/Open-Jev-Dev/blob/main/docs/model-provenance.md) for the fixed README,
+license and revision-API evidence. The inspected inventories contain no
+upstream `NOTICE` file; notices in additional bundled artifacts still apply.
+
+Open-Jev modifies the upstream model by training LoRA adapters and a scalar
+decision head, initially derived from the upstream Yes-minus-No embedding
+rows. Its published inference artifacts require the exact corresponding
+upstream weights and the Open-Jev loader. They are not unmodified Qwen models,
+standard text-generation checkpoints, or a reproduction of private Jev weights.
+
+The checkpoint packaging tool applies Apache-2.0 to its inference weight
+package and retains the upstream copyright and terms. Original Open-Jev source
+code remains under the repository MIT license, which is included separately
+when packaging. The generated data's CC0 markers do not license model weights.
+No checkpoint has been published merely by adding this notice or the packaging
+tool; an actual package must name its model revision, training run and measured
+results. No endorsement by Alibaba Cloud, the Qwen Team or TypeSafe is implied.

package/checkpoint/adapter/adapter_config.json

@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Qwen3_5TextModel",
+    "parent_library": "transformers.models.qwen3_5.modeling_qwen3_5"
+  },
+  "base_model_name_or_path": "",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.0,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.19.1",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "in_proj_qkv",
+    "q_proj",
+    "o_proj",
+    "out_proj",
+    "k_proj",
+    "v_proj"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

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+size 23613816

package/checkpoint/head.pt

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+size 18189

package/checkpoint/model.json

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+{
+  "model_id": "Qwen/Qwen3.5-9B",
+  "revision": "c202236235762e1c871ad0ccb60c8ee5ba337b9a",
+  "max_length": 4096,
+  "lora_rank": 8,
+  "method": "independent_candidate_lora_nll_brier"
+}

package/checkpoint/temperature.json

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+  "split": "calibration",
+  "n": 512,
+  "ids_sha256": "6ff7db59c1ae2485179b80316b3cb4f0161df77704692dcab48871a295ab94f1"
+}

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+  "kind": "local_inference_weight_package",
+  "weights_license": "Apache-2.0",
+  "model": "Qwen/Qwen3.5-9B",
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+  "files": {
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+  "scope": "All package files except this manifest are listed. Manifest SHA-256 is returned separately; no upload performed."
+}

package/provenance.json

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+  "schema_version": 1,
+  "weights_license": "Apache-2.0",
+  "code_license": "MIT",
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+  "excluded_evaluations": "No separate full-data, JF100, browser/drone pilot, simulator or closed-loop evaluation is imported."
+}

release-manifest.json

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+  "schema_version": 1,
+  "repo_id": "ZefanCai/Open-Jev-9B",
+  "artifact_type": "qwen_lora_adapter_plus_scalar_decision_head",
+  "base_model": "Qwen/Qwen3.5-9B",
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+  },
+  "scope": "All uploaded release payload files except release-manifest.json itself. The original Hub .gitattributes is repository metadata and is not part of this payload. Original package manifest paths are relative to package/."
+}