Stage unchanged Prism GGUF and Bev model card

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Ternary-Bonsai-2-27B-PQ2_0.gguf filter=lfs diff=lfs merge=lfs -text

LICENSE

@@ -0,0 +1,177 @@
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
+      and distribution as defined by Sections 1 through 9 of this document.
+
+      "Licensor" shall mean the copyright owner or entity authorized by
+      the copyright owner that is granting the License.
+
+      "Legal Entity" shall mean the union of the acting entity and all
+      other entities that control, are controlled by, or are under common
+      control with that entity. For the purposes of this definition,
+      "control" means (i) the power, direct or indirect, to cause the
+      direction or management of such entity, whether by contract or
+      otherwise, or (ii) ownership of fifty percent (50%) or more of the
+      outstanding shares, or (iii) beneficial ownership of such entity.
+
+      "You" (or "Your") shall mean an individual or Legal Entity
+      exercising permissions granted by this License.
+
+      "Source" form shall mean the preferred form for making modifications,
+      including but not limited to software source code, documentation
+      source, and configuration files.
+
+      "Object" form shall mean any form resulting from mechanical
+      transformation or translation of a Source form, including but
+      not limited to compiled object code, generated documentation,
+      and conversions to other media types.
+
+      "Work" shall mean the work of authorship, whether in Source or
+      Object form, made available under the License, as indicated by a
+      copyright notice that is included in or attached to the work
+      (an example is provided in the Appendix below).
+
+      "Derivative Works" shall mean any work, whether in Source or Object
+      form, that is based on (or derived from) the Work and for which the
+      editorial revisions, annotations, elaborations, or other modifications
+      represent, as a whole, an original work of authorship. For the purposes
+      of this License, Derivative Works shall not include works that remain
+      separable from, or merely link (or bind by name) to the interfaces of,
+      the Work and Derivative Works thereof.
+
+      "Contribution" shall mean any work of authorship, including
+      the original version of the Work and any modifications or additions
+      to that Work or Derivative Works thereof, that is intentionally
+      submitted to Licensor for inclusion in the Work by the copyright owner
+      or by an individual or Legal Entity authorized to submit on behalf of
+      the copyright owner. For the purposes of this definition, "submitted"
+      means any form of electronic, verbal, or written communication sent
+      to the Licensor or its representatives, including but not limited to
+      communication on electronic mailing lists, source code control systems,
+      and issue tracking systems that are managed by, or on behalf of, the
+      Licensor for the purpose of discussing and improving the Work, but
+      excluding communication that is conspicuously marked or otherwise
+      designated in writing by the copyright owner as "Not a Contribution."
+
+      "Contributor" shall mean Licensor and any individual or Legal Entity
+      on behalf of whom a Contribution has been received by Licensor and
+      subsequently incorporated within the Work.
+
+   2. Grant of Copyright License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      copyright license to reproduce, prepare Derivative Works of,
+      publicly display, publicly perform, sublicense, and distribute the
+      Work and such Derivative Works in Source or Object form.
+
+   3. Grant of Patent License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      (except as stated in this section) patent license to make, have made,
+      use, offer to sell, sell, import, and otherwise transfer the Work,
+      where such license applies only to those patent claims licensable
+      by such Contributor that are necessarily infringed by their
+      Contribution(s) alone or by combination of their Contribution(s)
+      with the Work to which such Contribution(s) was submitted. If You
+      institute patent litigation against any entity (including a
+      cross-claim or counterclaim in a lawsuit) alleging that the Work
+      or a Contribution incorporated within the Work constitutes direct
+      or contributory patent infringement, then any patent licenses
+      granted to You under this License for that Work shall terminate
+      as of the date such litigation is filed.
+
+   4. Redistribution. You may reproduce and distribute copies of the
+      Work or Derivative Works thereof in any medium, with or without
+      modifications, and in Source or Object form, provided that You
+      meet the following conditions:
+
+      (a) You must give any other recipients of the Work or
+          Derivative Works a copy of this License; and
+
+      (b) You must cause any modified files to carry prominent notices
+          stating that You changed the files; and
+
+      (c) You must retain, in the Source form of any Derivative Works
+          that You distribute, all copyright, patent, trademark, and
+          attribution notices from the Source form of the Work,
+          excluding those notices that do not pertain to any part of
+          the Derivative Works; and
+
+      (d) If the Work includes a "NOTICE" text file as part of its
+          distribution, then any Derivative Works that You distribute must
+          include a readable copy of the attribution notices contained
+          within such NOTICE file, excluding those notices that do not
+          pertain to any part of the Derivative Works, in at least one
+          of the following places: within a NOTICE text file distributed
+          as part of the Derivative Works; within the Source form or
+          documentation, if provided along with the Derivative Works; or,
+          within a display generated by the Derivative Works, if and
+          wherever such third-party notices normally appear. The contents
+          of the NOTICE file are for informational purposes only and
+          do not modify the License. You may add Your own attribution
+          notices within Derivative Works that You distribute, alongside
+          or as an addendum to the NOTICE text from the Work, provided
+          that such additional attribution notices cannot be construed
+          as modifying the License.
+
+      You may add Your own copyright statement to Your modifications and
+      may provide additional or different license terms and conditions
+      for use, reproduction, or distribution of Your modifications, or
+      for any such Derivative Works as a whole, provided Your use,
+      reproduction, and distribution of the Work otherwise complies with
+      the conditions stated in this License.
+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
+      Notwithstanding the above, nothing herein shall supersede or modify
+      the terms of any separate license agreement you may have executed
+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
+      names, trademarks, service marks, or product names of the Licensor,
+      except as required for reasonable and customary use in describing the
+      origin of the Work and reproducing the content of the NOTICE file.
+
+   7. Disclaimer of Warranty. Unless required by applicable law or
+      agreed to in writing, Licensor provides the Work (and each
+      Contributor provides its Contributions) on an "AS IS" BASIS,
+      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+      implied, including, without limitation, any warranties or conditions
+      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+      PARTICULAR PURPOSE. You are solely responsible for determining the
+      appropriateness of using or redistributing the Work and assume any
+      risks associated with Your exercise of permissions under this License.
+
+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
+      negligent acts) or agreed to in writing, shall any Contributor be
+      liable to You for damages, including any direct, indirect, special,
+      incidental, or consequential damages of any character arising as a
+      result of this License or out of the use or inability to use the
+      Work (including but not limited to damages for loss of goodwill,
+      work stoppage, computer failure or malfunction, or any and all
+      other commercial damages or losses), even if such Contributor
+      has been advised of the possibility of such damages.
+
+   9. Accepting Warranty or Additional Liability. While redistributing
+      the Work or Derivative Works thereof, You may choose to offer,
+      and charge a fee for, acceptance of support, warranty, indemnity,
+      or other liability obligations and/or rights consistent with this
+      License. However, in accepting such obligations, You may act only
+      on Your own behalf and on Your sole responsibility, not on behalf
+      of any other Contributor, and only if You agree to indemnify,
+      defend, and hold each Contributor harmless for any liability
+      incurred by, or claims asserted against, such Contributor by reason
+      of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+

NOTICE.txt

@@ -0,0 +1,4 @@
+This software is copyright 2026-present Prism ML, Inc. It is available under the Apache 2.0 license.
+If you publicly deploy or redistribute this software, we would appreciate attribution such as: "Created using Bonsai by Prism ML."
+
+This software is built from Qwen3.8-27B, Copyright 2026 Alibaba Cloud, which is available under the Apache 2.0 License: https://huggingface.co/Qwen/Qwen3.8-27B/blob/main/LICENSE

README.md

@@ -0,0 +1,119 @@
+---
+license: apache-2.0
+library_name: llama.cpp
+pipeline_tag: text-generation
+base_model: Qwen/Qwen3.8-27B
+base_model_relation: quantized
+language:
+- en
+- fa
+tags:
+- gguf
+- ternary
+- bonsai
+- decision-making
+- structured-output
+- zero-shot
+---
+
+# Bev
+
+**A ternary decision engine built around Jevfire-style one-token scoring.**
+
+[Code & documentation](https://github.com/Reza2kn/Bev) · [Release v0.1.1](https://github.com/Reza2kn/Bev/releases/tag/v0.1.1) · [Benchmarks](https://github.com/Reza2kn/Bev/blob/v0.1.1/docs/BENCHMARKS.md)
+
+**The GGUF in this repository is a byte-identical redistribution of [Prism ML's Ternary-Bonsai-2-27B](https://huggingface.co/prism-ml/Ternary-Bonsai-2-27B-gguf). Bev did not train or quantize these weights.** Prism supplies the ternary model, derived from Qwen3.8-27B. Bev adds a selected-token scoring extension, a local typed-decision API, portable setup, and measured evaluation. This is a model-and-software bundle, not a new fine-tune.
+
+## What Bev does
+
+Provide context and finite choices. Bev evaluates one next-token distribution per field, scores every candidate, and assembles structured JSON in Python. It supports:
+
+| Primitive | Result |
+|---|---|
+| Boolean / enum | A typed value from the allowed set |
+| Choice | The original option key and complete candidate probabilities |
+| Noul | Probability assigned to true |
+| Score | Probability-weighted position in an ordered rubric |
+
+The runtime supports 2–255 candidates per field. The validated serving configuration has two slots and 16,384 tokens per field. The API rejects oversized inputs and incomplete score sets explicitly.
+
+## Files and provenance
+
+| Item | Value |
+|---|---|
+| Weights | `Ternary-Bonsai-2-27B-PQ2_0.gguf` |
+| Size | **7,206,168,928 bytes** (7.21 GB; 6.71 GiB) |
+| SHA-256 | `3907dc1658db1f78a9826bf8d5bcb8dc65db0d466388937af57f2294fae62ec1` |
+| Immediate upstream | `prism-ml/Ternary-Bonsai-2-27B-gguf` |
+| Upstream revision | `6ed5e12bf84b7a63069882c91dd9e9218647d17b` |
+| Weight format | PQ2_0: ternary weights packed in two-bit slots with group scaling |
+| Bev training / LoRA / new quantization | None |
+| Weights license | Apache-2.0; original LICENSE and NOTICE.txt included |
+| Code license | MIT; complete attribution in the source bundle |
+
+The `model-manifest.json` records model/runtime pins and checksums. `bev-v0.1.1-source.tar.gz` contains the complete portable source, examples, tests, runtime patch, and documentation. The Python wheel packages the API only; the source installer is needed to set up the native backend. `SHA256SUMS` covers downloadable release artifacts.
+
+## Run it
+
+The supported setup for this release is **Linux x86_64 with an NVIDIA GPU and the pinned Prism CUDA 12.8 runtime**. It was validated on an RTX 5080 Laptop GPU with 16,303 MiB total memory. The serving process used about 8,504 MiB in one observation; this is not a peak-memory measurement or a hardware minimum guarantee.
+
+Use the [installation guide](https://github.com/Reza2kn/Bev/blob/v0.1.1/docs/INSTALL.md) for prerequisites, then:
+
+```sh
+git clone --branch v0.1.1 https://github.com/Reza2kn/Bev.git
+cd Bev
+bash scripts/install.sh
+bash scripts/start-services.sh
+
+curl --fail-with-body http://127.0.0.1:18781/v1/decisions \
+  -H 'Content-Type: application/json' \
+  --data-binary @examples/support-request.json
+```
+
+The support example returns `{"route":"billing"}` in `parsed_json`, alongside complete candidate scores. Interactive API documentation is served at `http://127.0.0.1:18781/docs`. The API binds to loopback by default.
+
+The installer verifies and downloads the original pinned Prism file. To use the identical copy from this repository instead, download it into the same model directory before installation:
+
+```sh
+export BEV_ROOT="${BEV_ROOT:-${XDG_DATA_HOME:-$HOME/.local/share}/bev}"
+hf download Reza2kn/Bev Ternary-Bonsai-2-27B-PQ2_0.gguf --local-dir "$BEV_ROOT/models"
+```
+
+This requires the Hugging Face CLI (`pip install huggingface_hub`). A generic GGUF viewer or stock upstream llama.cpp is not the validated runtime for PQ2_0. Use the pinned Prism fork and Bev adapter. This repository does not supply a Transformers classification head, a hosted inference endpoint, or a browser demo.
+
+## Persian evaluation
+
+On September 23, 2026, Bev v0.1.1 ran the complete [Jev Persian Benchmark](https://github.com/ArmanJR/Jev-Persian-Benchmark) at commit `ac218d96630da9d9cc08fd897868c4d3c7048b0d`, using the original dataset, question order, batches and scorer. All **624/624 answers** were valid across **106/106 completed requests**.
+
+| Main metric | Bev | Published Jev 1.13.0 reference |
+|---|---:|---:|
+| Choice: exact option | **229/240 · 95.42%** | 239/240 · 99.58% |
+| Noul: true when probability ≥0.5 | **152/160 · 95.00%** | 159/160 · 99.38% |
+| Score: within ±0.5 rubric levels | **70/80 · 87.50%** | 76/80 · 95.00% |
+| Choice Brier ↓ | 0.067756 | 0.0112 |
+| Noul Brier ↓ | 0.041239 | 0.0120 |
+| Score MAE, levels ↓ | 0.191233 | 0.0709 |
+
+Jev numbers are the benchmark author's published reference, not an independent Jev run here. The main evaluation has 480 questions; English and repeat diagnostics are separate. Bev had zero decision changes across 48 three-observation repeat groups, while some probabilities varied slightly. No training, prompt selection or calibration fitting used these cases.
+
+The measured median was **2.136 seconds per request** and total request time **224.03 seconds**. Main/repeat batches each have six questions. The hosted Jev reference and this laptop GPU have different hardware and serving conditions. No matched full-precision or ternary speedup comparison was performed.
+
+Aggregate results and provenance are included under `evaluations/`. Raw benchmark questions, gold labels, original scorer code, request journals and private host details are excluded. [Reproduction instructions](https://github.com/Reza2kn/Bev/blob/v0.1.1/docs/REPRODUCE.md) use the separately obtained upstream benchmark.
+
+## Limits and intended use
+
+Bev is intended for finite-label routing, classification and rubric evaluation where the application can define the allowed outputs. Fields are independent. Relative candidate probabilities are not calibrated confidence in correctness; confident mistakes occurred in evaluation.
+
+The Persian benchmark is synthetic and correlated, without independent human annotation. An earlier small general diagnostic scored **7/12 MMLU** and **2/10 SimpleBench**, alongside stronger results on other small subsets. Its loaded-source attestation was incomplete; the [full report](https://github.com/Reza2kn/Bev/blob/v0.1.1/docs/BENCHMARKS.md) retains this limitation. Neither run establishes broad reliability, Jev parity, or a Decision Index rank.
+
+One-token scoring can miss problems requiring multi-step reasoning, and the model inherits limitations and biases from its upstream models. A constrained output format does not guarantee a correct decision. No new calibration or independent production-domain validation is supplied by this release.
+
+## Attribution
+
+- **Jevfire / kikoncuo:** finite-choice scoring method and classification prompt, MIT.
+- **Prism ML:** Ternary-Bonsai-2 model and the Prism llama.cpp fork.
+- **Qwen / Alibaba Cloud:** Qwen3.8-27B base model.
+- **ArmanJR and Decision Index authors:** evaluation protocols and tools, obtained separately.
+- **Bev / Reza Sayar:** serving integration, typed API, packaging and evaluation, with OpenAI Codex assistance.
+
+This independent bundle does not imply affiliation or endorsement. The original Prism Apache-2.0 LICENSE and NOTICE are preserved with the weights; the source bundle includes all code notices.

Ternary-Bonsai-2-27B-PQ2_0.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3907dc1658db1f78a9826bf8d5bcb8dc65db0d466388937af57f2294fae62ec1
+size 7206168928

model-manifest.json

@@ -0,0 +1,29 @@
+{
+  "name": "Bev",
+  "version": "0.1.1",
+  "model_id": "prism-ml/Ternary-Bonsai-2-27B-gguf",
+  "model_revision": "6ed5e12bf84b7a63069882c91dd9e9218647d17b",
+  "model_file": "Ternary-Bonsai-2-27B-PQ2_0.gguf",
+  "model_bytes": 7206168928,
+  "model_sha256": "3907dc1658db1f78a9826bf8d5bcb8dc65db0d466388937af57f2294fae62ec1",
+  "packing": "PQ2_0, ternary weights with group scaling in two-bit slots",
+  "weights_modified": false,
+  "training_performed": false,
+  "jevfire_revision": "5df83b558bf635e006d31f8f2fc2798d0e3ff051",
+  "runtime_repository": "https://github.com/PrismML-Eng/llama.cpp",
+  "runtime_revision": "9a9394a895b96003ca842a6041cb28ac49a108f7",
+  "runtime_release": "prism-b10709-9a9394a",
+  "gpu": "NVIDIA GeForce RTX 5080 Laptop GPU",
+  "vram_mib": 16303,
+  "context_tokens_per_slot": 16384,
+  "parallel_slots": 2,
+  "runtime_patch_sha256": "7dadeaf5fccc2cb19c7c78e76173368168f9c904d7c88a6afe844722bba91cc2",
+  "runtime_archive_sha256": "8aec67eb023b251712c7e6490f367b5671bf587eced1436a9b85f4a90c3b7d3d",
+  "cuda_library_sha256": "a2f67b3e1a3fb476aba8b6fc1d2d2d7b25add3c4a169d77a679288492acc3762",
+  "model_vram_mib": 8504,
+  "weights_license": "Apache-2.0",
+  "code_license": "MIT",
+  "github": "https://github.com/Reza2kn/Bev",
+  "huggingface": "https://huggingface.co/Reza2kn/Bev",
+  "weight_relationship": "Byte-identical redistribution of the pinned Prism GGUF; no new training or quantization."
+}