Stage verified E2B model card and checksums privately

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NOTICE

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+Winnow-E2B
+
+Base model: Gemma 4 E2B IT by Google DeepMind
+Source: https://huggingface.co/google/gemma-4-E2B-it
+Source revision: 3e22461f65e89153144f8adb70e3b8c2cc9845a7
+Upstream license: Apache License, Version 2.0
+License reference: https://ai.google.dev/gemma/apache_2
+
+Winnow modifications are developed by EldanRing. The Q8_0 GGUF modifies the
+base through adapter fine-tuning, merging, and quantization. The matching F16
+vision projector accompanies it. Exact artifact identities are recorded in
+SHA256SUMS and release-manifest.json. The source training data and unmerged
+adapter are not included in this model repository.
+
+The optional official Gemma 4 E2B IT MTP assistant is by Google DeepMind under
+Apache License 2.0. Its pinned source and evaluated converted-file identity
+are documented in release-manifest.json. It is not bundled in this package.
+
+The separate Winnow inference repository builds on llama.cpp by Georgi
+Gerganov and contributors under the MIT license. No inference source or binary
+is included here. Winnow is an independent project; no upstream endorsement
+is implied.

README.md

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+---
+base_model: google/gemma-4-E2B-it
+base_model_relation: finetune
+license: apache-2.0
+library_name: gguf
+pipeline_tag: image-text-to-text
+tags:
+  - winnow
+  - gemma4
+  - local-inference
+  - gguf
+---
+
+# Winnow-E2B
+
+> **Release files pending.** The Q8 target and vision projector are not uploaded yet. Do not treat this repository as a complete download until both files appear and their Hub checksums match [SHA256SUMS](SHA256SUMS).
+
+Winnow-E2B is an EldanRing decision fine-tune of [Google's Gemma 4 E2B IT](https://huggingface.co/google/gemma-4-E2B-it). It scores the candidate answers supplied for each question through Winnow's native `/v1/systemone` API. It also supports ordinary text chat; image input requires the matching vision projector. Candidate probabilities are conditional on the supplied options, not a general guarantee of correctness.
+
+The Q8 GGUF contains the fine-tune merged into the language-model weights; no separate adapter or base-model download is needed. The source base revision is [`3e22461f65e89153144f8adb70e3b8c2cc9845a7`](https://huggingface.co/google/gemma-4-E2B-it/tree/3e22461f65e89153144f8adb70e3b8c2cc9845a7). The projector is the corresponding F16 vision export. Audio support has not been established for this package.
+
+## Exact model files
+
+| Role | File | Bytes | SHA-256 |
+|---|---|---:|---|
+| Q8 target | `gguf/Winnow-E2B-Q8_0.gguf` | 4,954,594,336 | `cb37414b46b5c4ac54ea9a44f71bb6147991c34e6be414a8cdd359cc10f0dfb1` |
+| F16 vision projector | `gguf/mmproj-Winnow-E2B.gguf` | 985,653,600 | `7faa5282cff7250380c191bdea4e13a7b397ad851e2d883873cd9c323a5e192f` |
+
+These hashes identify the **original files used in the E2B tests**. The shorter repository filenames are names for byte-identical copies. See the small [checksum file](SHA256SUMS) and [release manifest](release-manifest.json). Check both files after downloading; do not substitute an E4B or 12B model or projector.
+
+The optional MTP draft is Google's [official E2B IT assistant](https://huggingface.co/google/gemma-4-E2B-it-assistant/tree/2d874ef7d29f9a30599a1e4b3c1cbc9595f005df), revision `2d874ef7d29f9a30599a1e4b3c1cbc9595f005df`. The evaluated assistant was a CPU conversion of its `model.safetensors` (SHA-256 `93682eb1c97639d18f007704dc880bd74cbe530adaf7b1bb561213863fdad2a6`) to BF16 GGUF (170,194,016 bytes; SHA-256 `0772dcc50761a47a2da87151d3105ad2b82994d9dd1dae3ad3c5c0cd26086b16`). It is **not bundled here**. Download the pinned official source with:
+
+```sh
+huggingface-cli download google/gemma-4-E2B-it-assistant model.safetensors config.json tokenizer.json tokenizer_config.json generation_config.json --revision 2d874ef7d29f9a30599a1e4b3c1cbc9595f005df --local-dir gemma-4-E2B-it-assistant
+```
+
+The evaluated GGUF was produced with the pinned [`llama.cpp` converter revision `911f6cdc8ab8a530b2bee09ee61471a6f3178eeb`](https://github.com/ggml-org/llama.cpp/tree/911f6cdc8ab8a530b2bee09ee61471a6f3178eeb), using BF16 output. Verify the resulting file against the GGUF hash above before using MTP. A different conversion is a different artifact. Direct decisions and ordinary chat do not require the assistant.
+
+## Decision results
+
+The table evaluates the downloadable Q8 target, with its matching projector resident, on an RTX 5070 Ti. Direct is native candidate scoring. The experimental selective path uses raw direct maximum probability `<0.99` to trigger generated reasoning, then blends direct and augmented probabilities 50:50. It used F16 target KV, Q8 draft KV, the official BF16 assistant with MTP draft length 4, backend temperature sampling, one chat slot, and an 8,192-token context.
+
+| Panel | Direct | Selective reasoning |
+|---|---:|---:|
+| JevBench public, verified labels | 175/231 (75.8%) | 203/231 (87.9%) |
+| Kev v9 clean, verified labels | 728/1,046 (69.6%) | 851/1,046 (81.4%) |
+| Typed decisions, synthetic hard-teacher agreement | 1,237/2,000 (61.9%) | 1,365/2,000 (68.3%) |
+
+All three full panels were previously exposed during development, so these are regression and transfer results, not independent generalization estimates. In a separate 288-case disjoint holdout, the selective path gained only 3 agreements over the earlier transferred rule; its paired 95% interval included zero. Typed agreement is not independently verified correctness.
+
+For the three full panels in table order, mean serial API time was **0.051 → 1.368 s**, **0.023 → 1.233 s**, and **0.029 → 1.981 s** from direct to selective reasoning. These selective costs are paired-output replay estimates, not deployed-service timing or concurrent throughput. Generation length and fallback costs are included. The current integration's request-to-prompt mapping differs from the benchmark serialization, so these figures do not certify exact production-path equivalence.
+
+Image evidence is limited to a narrow 180-decision synthetic procedural panel. It does not establish photo, screenshot, or document quality. A 64K-context launch and small text/image requests were checked operationally; full-length 64K quality was not measured.
+
+## License and attribution
+
+Gemma 4 E2B IT and the separate official E2B IT assistant are by Google DeepMind under [Apache License 2.0](https://ai.google.dev/gemma/apache_2). Winnow modifications are by EldanRing. The [license](LICENSE) and [notice](NOTICE) apply to this model package. The optional assistant remains at Google's pinned repository and carries its own upstream attribution. The Winnow inference code is separately licensed; no inference binary or source is part of this model repository. No Google endorsement is implied.

SHA256SUMS

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+# Expected byte-identical release payloads. Upload pending; verify remote LFS/Xet hashes before considering the package complete.
+cb37414b46b5c4ac54ea9a44f71bb6147991c34e6be414a8cdd359cc10f0dfb1  gguf/Winnow-E2B-Q8_0.gguf
+7faa5282cff7250380c191bdea4e13a7b397ad851e2d883873cd9c323a5e192f  gguf/mmproj-Winnow-E2B.gguf

release-manifest.json

@@ -0,0 +1,50 @@
+{
+  "schema_version": 1,
+  "model_id": "EldanRing/Winnow-E2B",
+  "release_status": "private_staging_payload_pending",
+  "base_model": "google/gemma-4-E2B-it",
+  "base_revision": "3e22461f65e89153144f8adb70e3b8c2cc9845a7",
+  "source_adapter_sha256": "2923937bde82236a90b4d83819ede0885763e32b8d44f716fe6abbda52ce5292",
+  "license": "apache-2.0",
+  "artifacts": {
+    "q8_0": {
+      "path": "gguf/Winnow-E2B-Q8_0.gguf",
+      "original_evaluated_file": "Winnow-Gemma-4-E2B-Fresh26K-step1250-Q8_0.gguf",
+      "bytes": 4954594336,
+      "sha256": "cb37414b46b5c4ac54ea9a44f71bb6147991c34e6be414a8cdd359cc10f0dfb1",
+      "remote_status": "pending"
+    },
+    "projector_f16": {
+      "path": "gguf/mmproj-Winnow-E2B.gguf",
+      "original_evaluated_file": "mmproj-Winnow-Gemma-4-E2B-Fresh26K-step1250-F16.gguf",
+      "bytes": 985653600,
+      "sha256": "7faa5282cff7250380c191bdea4e13a7b397ad851e2d883873cd9c323a5e192f",
+      "remote_status": "pending"
+    }
+  },
+  "optional_assistant": {
+    "bundled": false,
+    "repository": "google/gemma-4-E2B-it-assistant",
+    "revision": "2d874ef7d29f9a30599a1e4b3c1cbc9595f005df",
+    "license": "apache-2.0",
+    "source_file": "model.safetensors",
+    "source_bytes": 157565344,
+    "source_sha256": "93682eb1c97639d18f007704dc880bd74cbe530adaf7b1bb561213863fdad2a6",
+    "evaluated_bf16_gguf_bytes": 170194016,
+    "evaluated_bf16_gguf_sha256": "0772dcc50761a47a2da87151d3105ad2b82994d9dd1dae3ad3c5c0cd26086b16",
+    "converter_revision": "911f6cdc8ab8a530b2bee09ee61471a6f3178eeb",
+    "converter_sha256": "e9a1da876330bbce9687541ab31736542a01b4ac43c6686126514a50f122fb7f"
+  },
+  "evaluated_profile": {
+    "target": "q8_0",
+    "context": 8192,
+    "target_kv": "f16",
+    "draft_kv": "q8_0",
+    "mtp_draft_length": 4,
+    "backend_temperature_sampling": true,
+    "raw_max_probability_gate": 0.99,
+    "direct_probability_weight": 0.5,
+    "augmented_probability_weight": 0.5,
+    "evidence_scope": "Previously exposed full text panels; current v2 integration prompt mapping differs from historical benchmark serialization."
+  }
+}