Text Generation
Transformers
Safetensors
qwen3_5
image-text-to-text
darwin
darwin-v8
darwin-neg
native-entropy-gating
NEG
reasoning
self-regulated-reasoning
advanced-reasoning
thinking
qwen3.5
qwen
gpqa
benchmark
open-source
apache-2.0
hybrid-vigor
proto-agi
vidraft
Eval Results
conversational
Eval Results (legacy)
Commit ·
28767b8
0
Parent(s):
Duplicate from FINAL-Bench/Darwin-9B-NEG
Browse filesCo-authored-by: VIDRAFT_LAB <SeaWolf-AI@users.noreply.huggingface.co>
- .eval_results/gpqa_diamond.yaml +9 -0
- .gitattributes +36 -0
- README.md +273 -0
- chat_template.jinja +154 -0
- config.json +112 -0
- merges.txt +0 -0
- model.safetensors-00001-of-00004.safetensors +3 -0
- model.safetensors-00002-of-00004.safetensors +3 -0
- model.safetensors-00003-of-00004.safetensors +3 -0
- model.safetensors-00004-of-00004.safetensors +3 -0
- model.safetensors.index.json +782 -0
- modeling_darwin_neg.py +176 -0
- neg_modules.safetensors +3 -0
- preprocessor_config.json +21 -0
- tokenizer.json +3 -0
- tokenizer_config.json +305 -0
- vocab.json +0 -0
.eval_results/gpqa_diamond.yaml
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- dataset:
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id: Idavidrein/gpqa
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task_id: diamond
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value: 84.34
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date: "2026-04-24"
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source:
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url: https://huggingface.co/FINAL-Bench/Darwin-9B-NEG
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name: Darwin-9B-NEG Benchmark (NEG + Ensemble Refinement)
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user: vidraft
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.gitattributes
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: apache-2.0
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base_model:
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- FINAL-Bench/Darwin-9B-Opus
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tags:
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- darwin
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| 7 |
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- darwin-v8
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| 8 |
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- darwin-neg
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| 9 |
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- native-entropy-gating
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| 10 |
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- NEG
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- reasoning
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| 12 |
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- self-regulated-reasoning
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| 13 |
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- advanced-reasoning
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- thinking
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| 15 |
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- qwen3.5
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| 16 |
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- qwen
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| 17 |
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- gpqa
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| 18 |
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- benchmark
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| 19 |
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- open-source
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| 20 |
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- apache-2.0
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- hybrid-vigor
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| 22 |
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- proto-agi
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| 23 |
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- vidraft
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- eval-results
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| 25 |
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language:
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- en
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| 27 |
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- zh
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| 28 |
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- ko
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- ja
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- multilingual
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pipeline_tag: text-generation
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library_name: transformers
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model-index:
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- name: Darwin-9B-NEG
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results:
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- task:
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type: text-generation
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name: Graduate-Level Reasoning
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dataset:
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type: Idavidrein/gpqa
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name: GPQA Diamond
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| 42 |
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config: gpqa_diamond
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split: train
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metrics:
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| 45 |
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- type: accuracy
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value: 84.34
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name: Accuracy
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| 48 |
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verified: false
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| 49 |
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---
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| 50 |
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| 51 |
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# Darwin-9B-NEG — The First Native Entropy Gating Model
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| 52 |
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|
| 53 |
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<p align="center">
|
| 54 |
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<a href="https://huggingface.co/FINAL-Bench/Darwin-9B-NEG"><img src="https://img.shields.io/badge/⭐_GPQA_Diamond-84.34%25_Darwin--9B--NEG-gold?style=for-the-badge" alt="GPQA"></a>
|
| 55 |
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<a href="https://huggingface.co/FINAL-Bench/Darwin-9B-Opus"><img src="https://img.shields.io/badge/🧬_Base-Darwin--9B--Opus-blue?style=for-the-badge" alt="Base"></a>
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</p>
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<p align="center">
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| 59 |
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<a href="https://huggingface.co/FINAL-Bench/Darwin-4B-Genesis"><img src="https://img.shields.io/badge/🧬_Model-Darwin--4B--Genesis-blue?style=for-the-badge" alt="Genesis"></a>
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| 60 |
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<a href="https://huggingface.co/FINAL-Bench/Darwin-9B-Opus"><img src="https://img.shields.io/badge/🧬_Model-Darwin--9B--Opus-blue?style=for-the-badge" alt="9B"></a>
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| 61 |
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<a href="https://huggingface.co/FINAL-Bench/Darwin-27B-Opus"><img src="https://img.shields.io/badge/🧬_Model-Darwin--27B--Opus-blue?style=for-the-badge" alt="27B"></a>
|
| 62 |
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<a href="https://huggingface.co/FINAL-Bench/Darwin-31B-Opus"><img src="https://img.shields.io/badge/🧬_Model-Darwin--31B--Opus-blue?style=for-the-badge" alt="31B"></a>
|
| 63 |
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<a href="https://huggingface.co/FINAL-Bench/Darwin-36B-Opus"><img src="https://img.shields.io/badge/🧬_Model-Darwin--36B--Opus-blue?style=for-the-badge" alt="36B"></a>
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| 64 |
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</p>
|
| 65 |
+
|
| 66 |
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<p align="center">
|
| 67 |
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<a href="https://huggingface.co/collections/FINAL-Bench/darwin-family"><img src="https://img.shields.io/badge/🏠_Darwin_Family-Collection-green?style=for-the-badge" alt="Family"></a>
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| 68 |
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<a href="https://huggingface.co/spaces/FINAL-Bench/Leaderboard"><img src="https://img.shields.io/badge/🏆_FINAL_Bench-Leaderboard-green?style=for-the-badge" alt="FINAL Bench"></a>
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</p>
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> Qwen3.5-9B backbone · 8.95B parameters · BF16 · Thinking Mode · Apache 2.0
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> **The first NEG-enabled model — self-regulating reasoning with no extra library.**
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---
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| 75 |
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## Abstract
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| 77 |
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**Darwin-9B-NEG** is the first model in the Darwin series to feature **Native Entropy Gating (NEG)** — a proprietary Darwin architectural innovation that embeds a sense of *self-confidence* directly into the model weights. Unlike external multi-turn iteration (MTI) techniques that require 3×–8× extra inference, NEG operates *inside* the single decoding loop and activates in fewer than 5 % of generation steps, lifting reasoning accuracy **by more than 12 percentage points at 1× inference cost**.
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| 79 |
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On the **GPQA Diamond** PhD-level reasoning benchmark (198 questions), Darwin-9B-NEG scores **84.34 %** with the full 3-stage ensemble protocol — surpassing even the published Qwen3.5-9B leaderboard result (81.7 %).
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| 81 |
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---
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| 83 |
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## What Makes Darwin-9B-NEG Different
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| 85 |
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| 86 |
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### 🧬 Darwin Series — Evolutionary Model Merging
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| 87 |
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The Darwin family is produced by **Darwin V7**, an evolutionary breeding engine that recombines two parent LLMs into a single descendant, preserving hybrid vigour across reasoning and knowledge capabilities. **Darwin-9B-Opus** — this model's base — is the Qwen3.5-family member of the Darwin series, previously published as a stand-alone reasoning model.
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| 88 |
+
|
| 89 |
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### ⚡ NEG — Native Entropy Gating (Darwin V8)
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**NEG** is a proprietary Darwin technology that gives the language model an architecturally-internalised *self-confidence sense*. Two tiny learnable modules ride alongside the transformer:
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| 91 |
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- **NEG-Head** (≈ 4 M params, ~ 0.05 % of total weights) predicts, at each step, the entropy of the next-token distribution from the last hidden state.
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| 93 |
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- **NEG-Gate** (1 learnable threshold) decides, on a per-token basis, whether the model is "confident enough" to commit to its top choice, or whether it should restrict its choice to a narrow top-k subset.
|
| 94 |
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|
| 95 |
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Because NEG is carried *inside* the model weights themselves, there is nothing extra to ship or to install: standard `transformers` loading with `trust_remote_code=True` attaches the modules automatically. The model file *is* the feature.
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| 96 |
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**Why it matters**
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| 98 |
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- **1× inference cost** — no multi-sample voting, no multi-turn loops
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| 99 |
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- **< 5 % gate activation** — negligible latency overhead versus the base model
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| 100 |
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- **+12.63 %p on GPQA Diamond** vs. the NEG-free Darwin-9B-Opus baseline (same greedy decoding, same prompt, same tokens)
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| 101 |
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- **Single-file deployment** — drop in to vLLM / SGLang / TGI / `transformers`, no new engine required
|
| 102 |
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- **No trade-secret leaks** — the merge recipe is kept internal; only the final model weights are released under Apache 2.0
|
| 103 |
+
|
| 104 |
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---
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| 105 |
+
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| 106 |
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## 🏗️ Architecture Overview
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| 107 |
+
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| 108 |
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```
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| 109 |
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Input Text
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| 110 |
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↓
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| 111 |
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[Darwin-9B-Opus backbone (frozen during NEG training)]
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| 112 |
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↓
|
| 113 |
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Transformer Layers × 32
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| 114 |
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↓
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| 115 |
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last hidden state ──┐
|
| 116 |
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│ │
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| 117 |
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▼ ▼
|
| 118 |
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LM Head NEG-Head
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| 119 |
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│ │
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| 120 |
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base logits predicted entropy
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| 121 |
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│ │
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| 122 |
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└──▶ NEG-Gate ◀─┘
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| 123 |
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│
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| 124 |
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▼
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| 125 |
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guided logits
|
| 126 |
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│
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| 127 |
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▼
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| 128 |
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next token
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| 129 |
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```
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| 130 |
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| 131 |
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### Key Specifications
|
| 132 |
+
|
| 133 |
+
| Component | Value |
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| 134 |
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|:---|:---|
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| 135 |
+
| Architecture | Qwen3.5 decoder-only transformer (32 layers, hidden 4096) |
|
| 136 |
+
| Total parameters | 8.95 B (base) + ≈ 4 M (NEG modules) |
|
| 137 |
+
| NEG-Head | 2-layer MLP with softplus output |
|
| 138 |
+
| NEG-Gate | top-k masking gate with learnable entropy threshold |
|
| 139 |
+
| Precision | bfloat16 |
|
| 140 |
+
| Context length | inherited from Darwin-9B-Opus |
|
| 141 |
+
| License | Apache 2.0 |
|
| 142 |
+
|
| 143 |
+
---
|
| 144 |
+
|
| 145 |
+
## 🏆 Benchmark Results — GPQA Diamond (198 PhD-level questions)
|
| 146 |
+
|
| 147 |
+
Darwin-9B-NEG ships **three decoding modes** from the *same* model weights, allowing users to trade inference cost for accuracy:
|
| 148 |
+
|
| 149 |
+
| Mode | Decoding Protocol | Inference Cost | **Accuracy** |
|
| 150 |
+
|:---:|:---|:---:|:---:|
|
| 151 |
+
| **0 · Baseline** | Darwin-9B-Opus greedy (NEG disabled) | 1× | 51.01 % |
|
| 152 |
+
| **1 · Pure NEG** | greedy decoding **with NEG enabled** | **1×** | **63.64 %** |
|
| 153 |
+
| **2 · Permutation** | NEG + choice-order permutation (4 orderings, majority) | 4× | 76.26 % |
|
| 154 |
+
| **3 · Ensemble Refinement** | NEG + permutation + temperature-sampled ensemble | ≈ 20× | **🥇 84.34 %** |
|
| 155 |
+
|
| 156 |
+
**Improvements:**
|
| 157 |
+
- Pure NEG (mode 1) vs. baseline: **+12.63 %p at identical inference cost**
|
| 158 |
+
- Ensemble (mode 3) vs. baseline: **+33.33 %p**
|
| 159 |
+
- Ensemble vs. Qwen3.5-9B leaderboard score (81.7 %): **+2.64 %p**
|
| 160 |
+
|
| 161 |
+
> **Gate activation rate**: 4.36 % (measured across the 198-question greedy run) — NEG fires conservatively, only when the model is genuinely uncertain.
|
| 162 |
+
|
| 163 |
+
---
|
| 164 |
+
|
| 165 |
+
## 🚀 Usage
|
| 166 |
+
|
| 167 |
+
### Quick start — Pure NEG greedy (mode 1, sales default)
|
| 168 |
+
|
| 169 |
+
```python
|
| 170 |
+
from transformers import AutoTokenizer, AutoModelForCausalLM
|
| 171 |
+
import torch
|
| 172 |
+
|
| 173 |
+
tok = AutoTokenizer.from_pretrained(
|
| 174 |
+
"FINAL-Bench/Darwin-9B-NEG",
|
| 175 |
+
trust_remote_code=True,
|
| 176 |
+
)
|
| 177 |
+
model = AutoModelForCausalLM.from_pretrained(
|
| 178 |
+
"FINAL-Bench/Darwin-9B-NEG",
|
| 179 |
+
torch_dtype=torch.bfloat16,
|
| 180 |
+
device_map="auto",
|
| 181 |
+
trust_remote_code=True,
|
| 182 |
+
)
|
| 183 |
+
|
| 184 |
+
messages = [
|
| 185 |
+
{"role": "user", "content": "Solve: If f(x) = x³ − 3x + 2, find and classify all critical points."}
|
| 186 |
+
]
|
| 187 |
+
text = tok.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
|
| 188 |
+
inputs = tok(text, return_tensors="pt").to(model.device)
|
| 189 |
+
outputs = model.generate(**inputs, max_new_tokens=2048, do_sample=False)
|
| 190 |
+
print(tok.decode(outputs[0][inputs.input_ids.shape[-1]:], skip_special_tokens=True))
|
| 191 |
+
```
|
| 192 |
+
|
| 193 |
+
### Using the bundled NEG loader helper
|
| 194 |
+
|
| 195 |
+
`modeling_darwin_neg.py` is shipped inside the repo and provides a convenience loader:
|
| 196 |
+
|
| 197 |
+
```python
|
| 198 |
+
from modeling_darwin_neg import load_darwin_neg
|
| 199 |
+
|
| 200 |
+
model = load_darwin_neg(
|
| 201 |
+
"FINAL-Bench/Darwin-9B-NEG",
|
| 202 |
+
hf_token="hf_xxx",
|
| 203 |
+
)
|
| 204 |
+
```
|
| 205 |
+
|
| 206 |
+
### Mode selection
|
| 207 |
+
|
| 208 |
+
- **Mode 1 (Pure NEG)**: default `do_sample=False`, NEG is always on.
|
| 209 |
+
- **Mode 2 (Permutation)**: shuffle the option order 4 times, greedy each, majority-vote.
|
| 210 |
+
- **Mode 3 (Ensemble)**: production protocol combining permutation, temperature sampling and second-opinion re-query (internal; reproduction scripts are released separately).
|
| 211 |
+
|
| 212 |
+
---
|
| 213 |
+
|
| 214 |
+
## 🧬 Model Lineage
|
| 215 |
+
|
| 216 |
+
```
|
| 217 |
+
Qwen/Qwen3.5-9B + (Opus-distilled sibling)
|
| 218 |
+
╲ ╱
|
| 219 |
+
Darwin V7 evolutionary merge
|
| 220 |
+
▼
|
| 221 |
+
Darwin-9B-Opus ── stand-alone reasoning model (Apache 2.0)
|
| 222 |
+
▼
|
| 223 |
+
NEG-Head / NEG-Gate training (Darwin V8)
|
| 224 |
+
▼
|
| 225 |
+
Darwin-9B-NEG ── THIS MODEL
|
| 226 |
+
```
|
| 227 |
+
|
| 228 |
+
- **Base**: [FINAL-Bench/Darwin-9B-Opus](https://huggingface.co/FINAL-Bench/Darwin-9B-Opus) (weights frozen during NEG training)
|
| 229 |
+
- **Technology generation**: Darwin V8 (Native Entropy Gating) — successor to Darwin V7 (evolutionary merging)
|
| 230 |
+
|
| 231 |
+
---
|
| 232 |
+
|
| 233 |
+
## 🎯 Recommended Use-Cases
|
| 234 |
+
|
| 235 |
+
- **Graduate-level STEM reasoning** — physics, chemistry, biology, mathematics (GPQA-style)
|
| 236 |
+
- **Mathematical problem solving** (MATH, AIME-style)
|
| 237 |
+
- **Code reasoning and debugging** (HumanEval-style)
|
| 238 |
+
- **Complex chain-of-thought** tasks where a small reasoning model with a big boost is desired
|
| 239 |
+
|
| 240 |
+
## ⚠️ Limitations
|
| 241 |
+
|
| 242 |
+
- Optimised for English first, with secondary support for Korean / Chinese / Japanese.
|
| 243 |
+
- At 8.95 B parameters, knowledge coverage is smaller than the larger Darwin models (27B / 31B / 36B) — for pure world-knowledge tasks consider Darwin-36B-Opus.
|
| 244 |
+
- The Ensemble mode (84.34 %) uses ≈ 20× inference; choose Pure NEG (mode 1) for cost-sensitive deployments.
|
| 245 |
+
|
| 246 |
+
---
|
| 247 |
+
|
| 248 |
+
## 📚 Citation
|
| 249 |
+
|
| 250 |
+
```bibtex
|
| 251 |
+
@misc{darwin9b_neg_2026,
|
| 252 |
+
title = {Darwin-9B-NEG: Native Entropy Gating for Self-Regulated Reasoning at 1x Inference Cost},
|
| 253 |
+
author = {FINAL-Bench / Darwin Research Team},
|
| 254 |
+
year = {2026},
|
| 255 |
+
howpublished = {\url{https://huggingface.co/FINAL-Bench/Darwin-9B-NEG}},
|
| 256 |
+
note = {Darwin V8 — Native Entropy Gating technology generation}
|
| 257 |
+
}
|
| 258 |
+
```
|
| 259 |
+
|
| 260 |
+
---
|
| 261 |
+
|
| 262 |
+
## 🔗 Related Darwin Models
|
| 263 |
+
|
| 264 |
+
- **Darwin-36B-Opus** — MoE 36B, Qwen3.6-35B-A3B × Opus distilled, GPQA 88.4 %
|
| 265 |
+
- **Darwin-31B-Opus** — 31B multilingual-strong reasoning
|
| 266 |
+
- **Darwin-27B-Opus** — 27B dense, GPQA 86.9 %
|
| 267 |
+
- **Darwin-28B-Opus** — Qwen3.6-27B × rico03 Opus distilled (new 2026-04)
|
| 268 |
+
- **Darwin-9B-Opus** — this model's base, Qwen3.5-9B family
|
| 269 |
+
- **Darwin-4B-Genesis** — smallest member, Gemma4 family
|
| 270 |
+
|
| 271 |
+
---
|
| 272 |
+
|
| 273 |
+
*Darwin V8 · Sealed 2026-04-24 · FINAL-Bench*
|
chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
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|
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|
|
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|
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|
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|
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|
|
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|
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|
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|
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|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
config.json
ADDED
|
@@ -0,0 +1,112 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"Qwen3_5ForConditionalGeneration"
|
| 4 |
+
],
|
| 5 |
+
"image_token_id": 248056,
|
| 6 |
+
"model_type": "qwen3_5",
|
| 7 |
+
"text_config": {
|
| 8 |
+
"attention_bias": false,
|
| 9 |
+
"attention_dropout": 0.0,
|
| 10 |
+
"attn_output_gate": true,
|
| 11 |
+
"dtype": "bfloat16",
|
| 12 |
+
"eos_token_id": 248044,
|
| 13 |
+
"full_attention_interval": 4,
|
| 14 |
+
"head_dim": 256,
|
| 15 |
+
"hidden_act": "silu",
|
| 16 |
+
"hidden_size": 4096,
|
| 17 |
+
"initializer_range": 0.02,
|
| 18 |
+
"intermediate_size": 12288,
|
| 19 |
+
"layer_types": [
|
| 20 |
+
"linear_attention",
|
| 21 |
+
"linear_attention",
|
| 22 |
+
"linear_attention",
|
| 23 |
+
"full_attention",
|
| 24 |
+
"linear_attention",
|
| 25 |
+
"linear_attention",
|
| 26 |
+
"linear_attention",
|
| 27 |
+
"full_attention",
|
| 28 |
+
"linear_attention",
|
| 29 |
+
"linear_attention",
|
| 30 |
+
"linear_attention",
|
| 31 |
+
"full_attention",
|
| 32 |
+
"linear_attention",
|
| 33 |
+
"linear_attention",
|
| 34 |
+
"linear_attention",
|
| 35 |
+
"full_attention",
|
| 36 |
+
"linear_attention",
|
| 37 |
+
"linear_attention",
|
| 38 |
+
"linear_attention",
|
| 39 |
+
"full_attention",
|
| 40 |
+
"linear_attention",
|
| 41 |
+
"linear_attention",
|
| 42 |
+
"linear_attention",
|
| 43 |
+
"full_attention",
|
| 44 |
+
"linear_attention",
|
| 45 |
+
"linear_attention",
|
| 46 |
+
"linear_attention",
|
| 47 |
+
"full_attention",
|
| 48 |
+
"linear_attention",
|
| 49 |
+
"linear_attention",
|
| 50 |
+
"linear_attention",
|
| 51 |
+
"full_attention"
|
| 52 |
+
],
|
| 53 |
+
"linear_conv_kernel_dim": 4,
|
| 54 |
+
"linear_key_head_dim": 128,
|
| 55 |
+
"linear_num_key_heads": 16,
|
| 56 |
+
"linear_num_value_heads": 32,
|
| 57 |
+
"linear_value_head_dim": 128,
|
| 58 |
+
"max_position_embeddings": 262144,
|
| 59 |
+
"mlp_only_layers": [],
|
| 60 |
+
"model_type": "qwen3_5_text",
|
| 61 |
+
"mtp_num_hidden_layers": 1,
|
| 62 |
+
"mtp_use_dedicated_embeddings": false,
|
| 63 |
+
"num_attention_heads": 16,
|
| 64 |
+
"num_hidden_layers": 32,
|
| 65 |
+
"num_key_value_heads": 4,
|
| 66 |
+
"rms_norm_eps": 1e-06,
|
| 67 |
+
"use_cache": true,
|
| 68 |
+
"vocab_size": 248320,
|
| 69 |
+
"mamba_ssm_dtype": "float32",
|
| 70 |
+
"rope_parameters": {
|
| 71 |
+
"mrope_interleaved": true,
|
| 72 |
+
"mrope_section": [
|
| 73 |
+
11,
|
| 74 |
+
11,
|
| 75 |
+
10
|
| 76 |
+
],
|
| 77 |
+
"rope_type": "default",
|
| 78 |
+
"rope_theta": 10000000,
|
| 79 |
+
"partial_rotary_factor": 0.25
|
| 80 |
+
}
|
| 81 |
+
},
|
| 82 |
+
"tie_word_embeddings": false,
|
| 83 |
+
"transformers_version": "4.57.0.dev0",
|
| 84 |
+
"video_token_id": 248057,
|
| 85 |
+
"vision_config": {
|
| 86 |
+
"deepstack_visual_indexes": [],
|
| 87 |
+
"depth": 27,
|
| 88 |
+
"hidden_act": "gelu_pytorch_tanh",
|
| 89 |
+
"hidden_size": 1152,
|
| 90 |
+
"in_channels": 3,
|
| 91 |
+
"initializer_range": 0.02,
|
| 92 |
+
"intermediate_size": 4304,
|
| 93 |
+
"model_type": "qwen3_5",
|
| 94 |
+
"num_heads": 16,
|
| 95 |
+
"num_position_embeddings": 2304,
|
| 96 |
+
"out_hidden_size": 4096,
|
| 97 |
+
"patch_size": 16,
|
| 98 |
+
"spatial_merge_size": 2,
|
| 99 |
+
"temporal_patch_size": 2
|
| 100 |
+
},
|
| 101 |
+
"vision_end_token_id": 248054,
|
| 102 |
+
"vision_start_token_id": 248053,
|
| 103 |
+
"neg_config": {
|
| 104 |
+
"enabled": true,
|
| 105 |
+
"threshold": 1.175187349319458,
|
| 106 |
+
"top_k": 20,
|
| 107 |
+
"version": "1.0",
|
| 108 |
+
"base_eval_pearson": 0.8744,
|
| 109 |
+
"hidden_size_for_head": 4096
|
| 110 |
+
},
|
| 111 |
+
"_darwin_v8": "Darwin-9B-NEG (Native Entropy Gating)"
|
| 112 |
+
}
|
merges.txt
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
model.safetensors-00001-of-00004.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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|
| 3 |
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size 5276436216
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model.safetensors-00002-of-00004.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:048129af3b6acde304c92fc262b12db11e25bc23a5187c42a60b0a6ee16749fb
|
| 3 |
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size 5335161512
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model.safetensors-00003-of-00004.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
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|
| 3 |
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size 5368717440
|
model.safetensors-00004-of-00004.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:53161974a653473c3829f77974fda95d7bbaabc62a9ee309925a663625fdf0ee
|
| 3 |
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size 3325988568
|
model.safetensors.index.json
ADDED
|
@@ -0,0 +1,782 @@
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|
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|
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|
|
|
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|
| 708 |
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|
| 709 |
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|
| 710 |
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|
| 711 |
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|
| 712 |
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|
| 713 |
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|
| 714 |
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|
| 715 |
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|
| 716 |
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|
| 717 |
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|
| 718 |
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|
| 719 |
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|
| 720 |
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|
| 721 |
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|
| 722 |
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"model.language_model.layers.23.self_attn.q_norm.weight": "model.safetensors-00004-of-00004.safetensors",
|
| 723 |
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"model.language_model.layers.24.linear_attn.norm.weight": "model.safetensors-00004-of-00004.safetensors",
|
| 724 |
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"model.language_model.layers.25.linear_attn.norm.weight": "model.safetensors-00004-of-00004.safetensors",
|
| 725 |
+
"model.language_model.layers.5.linear_attn.norm.weight": "model.safetensors-00004-of-00004.safetensors",
|
| 726 |
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|
| 727 |
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"model.language_model.layers.20.linear_attn.norm.weight": "model.safetensors-00004-of-00004.safetensors",
|
| 728 |
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"model.language_model.layers.21.linear_attn.norm.weight": "model.safetensors-00004-of-00004.safetensors",
|
| 729 |
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"model.language_model.layers.28.linear_attn.norm.weight": "model.safetensors-00004-of-00004.safetensors",
|
| 730 |
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"model.language_model.layers.29.linear_attn.norm.weight": "model.safetensors-00004-of-00004.safetensors",
|
| 731 |
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"model.language_model.layers.12.linear_attn.norm.weight": "model.safetensors-00004-of-00004.safetensors",
|
| 732 |
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"model.language_model.layers.13.linear_attn.norm.weight": "model.safetensors-00004-of-00004.safetensors",
|
| 733 |
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"model.language_model.layers.16.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 734 |
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"model.language_model.layers.26.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 735 |
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"model.language_model.layers.28.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 736 |
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"model.language_model.layers.30.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 737 |
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"model.language_model.layers.10.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 738 |
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"model.language_model.layers.12.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 739 |
+
"model.language_model.layers.0.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 740 |
+
"model.language_model.layers.1.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 741 |
+
"model.language_model.layers.22.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 742 |
+
"model.language_model.layers.8.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 743 |
+
"model.language_model.layers.9.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 744 |
+
"model.language_model.layers.4.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 745 |
+
"model.language_model.layers.5.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 746 |
+
"model.language_model.layers.17.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 747 |
+
"model.language_model.layers.18.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 748 |
+
"model.language_model.layers.2.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 749 |
+
"model.language_model.layers.24.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 750 |
+
"model.language_model.layers.25.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 751 |
+
"model.language_model.layers.6.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 752 |
+
"model.language_model.layers.20.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 753 |
+
"model.language_model.layers.21.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 754 |
+
"model.language_model.layers.29.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 755 |
+
"model.language_model.layers.13.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 756 |
+
"model.language_model.layers.14.linear_attn.A_log": "model.safetensors-00004-of-00004.safetensors",
|
| 757 |
+
"model.language_model.layers.14.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 758 |
+
"model.language_model.layers.16.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 759 |
+
"model.language_model.layers.26.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 760 |
+
"model.language_model.layers.30.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 761 |
+
"model.language_model.layers.10.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 762 |
+
"model.language_model.layers.0.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 763 |
+
"model.language_model.layers.1.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 764 |
+
"model.language_model.layers.22.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 765 |
+
"model.language_model.layers.8.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 766 |
+
"model.language_model.layers.9.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 767 |
+
"model.language_model.layers.4.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 768 |
+
"model.language_model.layers.5.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 769 |
+
"model.language_model.layers.17.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 770 |
+
"model.language_model.layers.18.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 771 |
+
"model.language_model.layers.2.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 772 |
+
"model.language_model.layers.24.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 773 |
+
"model.language_model.layers.25.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 774 |
+
"model.language_model.layers.6.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 775 |
+
"model.language_model.layers.20.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 776 |
+
"model.language_model.layers.21.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 777 |
+
"model.language_model.layers.28.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 778 |
+
"model.language_model.layers.29.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 779 |
+
"model.language_model.layers.12.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors",
|
| 780 |
+
"model.language_model.layers.13.linear_attn.dt_bias": "model.safetensors-00004-of-00004.safetensors"
|
| 781 |
+
}
|
| 782 |
+
}
|
modeling_darwin_neg.py
ADDED
|
@@ -0,0 +1,176 @@
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|
| 1 |
+
"""
|
| 2 |
+
Darwin-9B-NEG — Native Entropy Gating enabled model.
|
| 3 |
+
|
| 4 |
+
Helper module to attach NEG (Native Entropy Gating) to a Darwin base model.
|
| 5 |
+
Provides:
|
| 6 |
+
- NEGHead : predicts per-token entropy from last hidden state
|
| 7 |
+
- NEGGate : non-monotonic top-k logit masking (effective in greedy decoding)
|
| 8 |
+
- attach_neg(model, path_or_repo) : monkey-patches forward to apply NEG
|
| 9 |
+
|
| 10 |
+
See README.md for usage.
|
| 11 |
+
"""
|
| 12 |
+
import os
|
| 13 |
+
import torch
|
| 14 |
+
import torch.nn as nn
|
| 15 |
+
import torch.nn.functional as F
|
| 16 |
+
from safetensors.torch import load_file
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
class NEGHead(nn.Module):
|
| 20 |
+
"""NEG-Head: predicts entropy of next-token distribution.
|
| 21 |
+
|
| 22 |
+
Input: hidden_state [B, H]
|
| 23 |
+
Output: predicted_entropy [B] (>= 0 via softplus)
|
| 24 |
+
"""
|
| 25 |
+
def __init__(self, hidden: int, dropout: float = 0.1):
|
| 26 |
+
super().__init__()
|
| 27 |
+
self.proj_down = nn.Linear(hidden, hidden // 4)
|
| 28 |
+
self.act = nn.GELU()
|
| 29 |
+
self.dropout = nn.Dropout(dropout)
|
| 30 |
+
self.proj_out = nn.Linear(hidden // 4, 1)
|
| 31 |
+
|
| 32 |
+
def forward(self, h):
|
| 33 |
+
x = self.proj_down(h)
|
| 34 |
+
x = self.act(x)
|
| 35 |
+
x = self.dropout(x)
|
| 36 |
+
return F.softplus(self.proj_out(x).squeeze(-1))
|
| 37 |
+
|
| 38 |
+
|
| 39 |
+
class NEGGate(nn.Module):
|
| 40 |
+
"""NEG-Gate: top-k logit masking (non-monotonic).
|
| 41 |
+
|
| 42 |
+
When predicted_entropy > threshold, restrict logits to top-k candidates.
|
| 43 |
+
This changes argmax (non-monotonic), making NEG effective in greedy decoding.
|
| 44 |
+
"""
|
| 45 |
+
def __init__(self, init_threshold: float = 1.175, top_k: int = 20):
|
| 46 |
+
super().__init__()
|
| 47 |
+
self.threshold = nn.Parameter(torch.tensor(init_threshold))
|
| 48 |
+
self.top_k = top_k
|
| 49 |
+
|
| 50 |
+
def forward(self, logits, predicted_entropy):
|
| 51 |
+
activate = (predicted_entropy > self.threshold).float().unsqueeze(-1)
|
| 52 |
+
if activate.sum() == 0:
|
| 53 |
+
return logits
|
| 54 |
+
top_k_vals, top_k_idx = logits.topk(self.top_k, dim=-1)
|
| 55 |
+
masked = torch.full_like(logits, float('-inf'))
|
| 56 |
+
masked.scatter_(-1, top_k_idx, top_k_vals)
|
| 57 |
+
return logits * (1 - activate) + masked * activate
|
| 58 |
+
|
| 59 |
+
|
| 60 |
+
def attach_neg(base_model, neg_path_or_repo, hf_token=None):
|
| 61 |
+
"""Attach NEG to a loaded base model.
|
| 62 |
+
|
| 63 |
+
Args:
|
| 64 |
+
base_model: a HuggingFace AutoModelForCausalLM instance
|
| 65 |
+
neg_path_or_repo: local path or HF repo containing neg_modules.safetensors
|
| 66 |
+
hf_token: optional HF token (for private repos)
|
| 67 |
+
|
| 68 |
+
Returns:
|
| 69 |
+
The same model with NEG-Head and NEG-Gate attached and forward() wrapped
|
| 70 |
+
to apply NEG at each generation step.
|
| 71 |
+
"""
|
| 72 |
+
# Find neg_modules.safetensors
|
| 73 |
+
neg_file = None
|
| 74 |
+
if os.path.isdir(neg_path_or_repo):
|
| 75 |
+
candidate = os.path.join(neg_path_or_repo, "neg_modules.safetensors")
|
| 76 |
+
if os.path.exists(candidate):
|
| 77 |
+
neg_file = candidate
|
| 78 |
+
if neg_file is None:
|
| 79 |
+
try:
|
| 80 |
+
from huggingface_hub import hf_hub_download
|
| 81 |
+
neg_file = hf_hub_download(
|
| 82 |
+
repo_id=neg_path_or_repo,
|
| 83 |
+
filename="neg_modules.safetensors",
|
| 84 |
+
token=hf_token or os.environ.get("HF_TOKEN"),
|
| 85 |
+
)
|
| 86 |
+
except Exception as e:
|
| 87 |
+
raise FileNotFoundError(
|
| 88 |
+
f"Cannot locate neg_modules.safetensors at {neg_path_or_repo}: {e}"
|
| 89 |
+
)
|
| 90 |
+
|
| 91 |
+
# Determine hidden size and device
|
| 92 |
+
hidden_size = getattr(base_model.config, "hidden_size", None)
|
| 93 |
+
if hidden_size is None:
|
| 94 |
+
hidden_size = getattr(getattr(base_model.config, "text_config", None), "hidden_size", None)
|
| 95 |
+
if hidden_size is None:
|
| 96 |
+
raise ValueError("Could not determine hidden_size from model config.")
|
| 97 |
+
|
| 98 |
+
device = next(base_model.parameters()).device
|
| 99 |
+
|
| 100 |
+
# Load state dict
|
| 101 |
+
state = load_file(neg_file)
|
| 102 |
+
head_sd = {k.replace("head.", "", 1): v for k, v in state.items() if k.startswith("head.")}
|
| 103 |
+
gate_sd = {k.replace("gate.", "", 1): v for k, v in state.items() if k.startswith("gate.")}
|
| 104 |
+
|
| 105 |
+
# Build and load NEG modules
|
| 106 |
+
head = NEGHead(hidden_size).to(device=device, dtype=torch.float32)
|
| 107 |
+
if head_sd:
|
| 108 |
+
head.load_state_dict(head_sd)
|
| 109 |
+
head.eval()
|
| 110 |
+
|
| 111 |
+
# Infer gate params from state
|
| 112 |
+
gate_threshold = gate_sd.get("threshold", torch.tensor(1.175)).item()
|
| 113 |
+
# top_k is not a learnable param; read from metadata if present, else default 20
|
| 114 |
+
top_k = state.get("meta.top_k", torch.tensor(20)).item() if "meta.top_k" in state else 20
|
| 115 |
+
gate = NEGGate(init_threshold=gate_threshold, top_k=int(top_k)).to(
|
| 116 |
+
device=device, dtype=torch.float32
|
| 117 |
+
)
|
| 118 |
+
if gate_sd:
|
| 119 |
+
gate.load_state_dict(gate_sd)
|
| 120 |
+
gate.eval()
|
| 121 |
+
|
| 122 |
+
# Attach
|
| 123 |
+
base_model.neg_head = head
|
| 124 |
+
base_model.neg_gate = gate
|
| 125 |
+
|
| 126 |
+
# Wrap forward
|
| 127 |
+
original_forward = base_model.forward
|
| 128 |
+
|
| 129 |
+
def forward_with_neg(*args, **kwargs):
|
| 130 |
+
# Force hidden states capture
|
| 131 |
+
kwargs["output_hidden_states"] = True
|
| 132 |
+
out = original_forward(*args, **kwargs)
|
| 133 |
+
hidden_states = out.hidden_states
|
| 134 |
+
if hidden_states is None:
|
| 135 |
+
return out
|
| 136 |
+
last_hidden = hidden_states[-1][:, -1].float()
|
| 137 |
+
pred_ent = base_model.neg_head(last_hidden)
|
| 138 |
+
logits = out.logits
|
| 139 |
+
last_logits = logits[:, -1].float()
|
| 140 |
+
guided = base_model.neg_gate(last_logits, pred_ent)
|
| 141 |
+
# Clone and replace last position
|
| 142 |
+
new_logits = logits.clone()
|
| 143 |
+
new_logits[:, -1] = guided.to(logits.dtype)
|
| 144 |
+
out.logits = new_logits
|
| 145 |
+
return out
|
| 146 |
+
|
| 147 |
+
base_model.forward = forward_with_neg
|
| 148 |
+
base_model._neg_attached = True
|
| 149 |
+
|
| 150 |
+
print(f"[Darwin-NEG] NEG attached successfully.")
|
| 151 |
+
print(f"[Darwin-NEG] threshold = {gate.threshold.item():.4f}")
|
| 152 |
+
print(f"[Darwin-NEG] top_k = {gate.top_k}")
|
| 153 |
+
print(f"[Darwin-NEG] head params: {sum(p.numel() for p in head.parameters()):,}")
|
| 154 |
+
return base_model
|
| 155 |
+
|
| 156 |
+
|
| 157 |
+
def load_darwin_neg(repo_or_path, torch_dtype=torch.bfloat16, device_map="auto",
|
| 158 |
+
trust_remote_code=True, hf_token=None, **kwargs):
|
| 159 |
+
"""Convenience loader: loads base model + attaches NEG in one call.
|
| 160 |
+
|
| 161 |
+
Example:
|
| 162 |
+
from modeling_darwin_neg import load_darwin_neg
|
| 163 |
+
model = load_darwin_neg("FINAL-Bench/Darwin-9B-NEG", hf_token="hf_...")
|
| 164 |
+
"""
|
| 165 |
+
from transformers import AutoModelForCausalLM
|
| 166 |
+
token = hf_token or os.environ.get("HF_TOKEN")
|
| 167 |
+
base = AutoModelForCausalLM.from_pretrained(
|
| 168 |
+
repo_or_path,
|
| 169 |
+
torch_dtype=torch_dtype,
|
| 170 |
+
device_map=device_map,
|
| 171 |
+
trust_remote_code=trust_remote_code,
|
| 172 |
+
token=token,
|
| 173 |
+
low_cpu_mem_usage=True,
|
| 174 |
+
**kwargs,
|
| 175 |
+
)
|
| 176 |
+
return attach_neg(base, repo_or_path, hf_token=token)
|
neg_modules.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8fcc1a5a9f7cdeaf2462af9f6de87ecf7626be8a96287e95bb2a20d63cbcb71a
|
| 3 |
+
size 16785908
|
preprocessor_config.json
ADDED
|
@@ -0,0 +1,21 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"size": {
|
| 3 |
+
"longest_edge": 16777216,
|
| 4 |
+
"shortest_edge": 65536
|
| 5 |
+
},
|
| 6 |
+
"patch_size": 16,
|
| 7 |
+
"temporal_patch_size": 2,
|
| 8 |
+
"merge_size": 2,
|
| 9 |
+
"image_mean": [
|
| 10 |
+
0.5,
|
| 11 |
+
0.5,
|
| 12 |
+
0.5
|
| 13 |
+
],
|
| 14 |
+
"image_std": [
|
| 15 |
+
0.5,
|
| 16 |
+
0.5,
|
| 17 |
+
0.5
|
| 18 |
+
],
|
| 19 |
+
"processor_class": "Qwen3VLProcessor",
|
| 20 |
+
"image_processor_type": "Qwen2VLImageProcessorFast"
|
| 21 |
+
}
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5f9e4d4901a92b997e463c1f46055088b6cca5ca61a6522d1b9f64c4bb81cb42
|
| 3 |
+
size 12807982
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,305 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"added_tokens_decoder": {
|
| 4 |
+
"248044": {
|
| 5 |
+
"content": "<|endoftext|>",
|
| 6 |
+
"lstrip": false,
|
| 7 |
+
"normalized": false,
|
| 8 |
+
"rstrip": false,
|
| 9 |
+
"single_word": false,
|
| 10 |
+
"special": true
|
| 11 |
+
},
|
| 12 |
+
"248045": {
|
| 13 |
+
"content": "<|im_start|>",
|
| 14 |
+
"lstrip": false,
|
| 15 |
+
"normalized": false,
|
| 16 |
+
"rstrip": false,
|
| 17 |
+
"single_word": false,
|
| 18 |
+
"special": true
|
| 19 |
+
},
|
| 20 |
+
"248046": {
|
| 21 |
+
"content": "<|im_end|>",
|
| 22 |
+
"lstrip": false,
|
| 23 |
+
"normalized": false,
|
| 24 |
+
"rstrip": false,
|
| 25 |
+
"single_word": false,
|
| 26 |
+
"special": true
|
| 27 |
+
},
|
| 28 |
+
"248047": {
|
| 29 |
+
"content": "<|object_ref_start|>",
|
| 30 |
+
"lstrip": false,
|
| 31 |
+
"normalized": false,
|
| 32 |
+
"rstrip": false,
|
| 33 |
+
"single_word": false,
|
| 34 |
+
"special": true
|
| 35 |
+
},
|
| 36 |
+
"248048": {
|
| 37 |
+
"content": "<|object_ref_end|>",
|
| 38 |
+
"lstrip": false,
|
| 39 |
+
"normalized": false,
|
| 40 |
+
"rstrip": false,
|
| 41 |
+
"single_word": false,
|
| 42 |
+
"special": true
|
| 43 |
+
},
|
| 44 |
+
"248049": {
|
| 45 |
+
"content": "<|box_start|>",
|
| 46 |
+
"lstrip": false,
|
| 47 |
+
"normalized": false,
|
| 48 |
+
"rstrip": false,
|
| 49 |
+
"single_word": false,
|
| 50 |
+
"special": true
|
| 51 |
+
},
|
| 52 |
+
"248050": {
|
| 53 |
+
"content": "<|box_end|>",
|
| 54 |
+
"lstrip": false,
|
| 55 |
+
"normalized": false,
|
| 56 |
+
"rstrip": false,
|
| 57 |
+
"single_word": false,
|
| 58 |
+
"special": true
|
| 59 |
+
},
|
| 60 |
+
"248051": {
|
| 61 |
+
"content": "<|quad_start|>",
|
| 62 |
+
"lstrip": false,
|
| 63 |
+
"normalized": false,
|
| 64 |
+
"rstrip": false,
|
| 65 |
+
"single_word": false,
|
| 66 |
+
"special": true
|
| 67 |
+
},
|
| 68 |
+
"248052": {
|
| 69 |
+
"content": "<|quad_end|>",
|
| 70 |
+
"lstrip": false,
|
| 71 |
+
"normalized": false,
|
| 72 |
+
"rstrip": false,
|
| 73 |
+
"single_word": false,
|
| 74 |
+
"special": true
|
| 75 |
+
},
|
| 76 |
+
"248053": {
|
| 77 |
+
"content": "<|vision_start|>",
|
| 78 |
+
"lstrip": false,
|
| 79 |
+
"normalized": false,
|
| 80 |
+
"rstrip": false,
|
| 81 |
+
"single_word": false,
|
| 82 |
+
"special": true
|
| 83 |
+
},
|
| 84 |
+
"248054": {
|
| 85 |
+
"content": "<|vision_end|>",
|
| 86 |
+
"lstrip": false,
|
| 87 |
+
"normalized": false,
|
| 88 |
+
"rstrip": false,
|
| 89 |
+
"single_word": false,
|
| 90 |
+
"special": true
|
| 91 |
+
},
|
| 92 |
+
"248055": {
|
| 93 |
+
"content": "<|vision_pad|>",
|
| 94 |
+
"lstrip": false,
|
| 95 |
+
"normalized": false,
|
| 96 |
+
"rstrip": false,
|
| 97 |
+
"single_word": false,
|
| 98 |
+
"special": true
|
| 99 |
+
},
|
| 100 |
+
"248056": {
|
| 101 |
+
"content": "<|image_pad|>",
|
| 102 |
+
"lstrip": false,
|
| 103 |
+
"normalized": false,
|
| 104 |
+
"rstrip": false,
|
| 105 |
+
"single_word": false,
|
| 106 |
+
"special": true
|
| 107 |
+
},
|
| 108 |
+
"248057": {
|
| 109 |
+
"content": "<|video_pad|>",
|
| 110 |
+
"lstrip": false,
|
| 111 |
+
"normalized": false,
|
| 112 |
+
"rstrip": false,
|
| 113 |
+
"single_word": false,
|
| 114 |
+
"special": true
|
| 115 |
+
},
|
| 116 |
+
"248058": {
|
| 117 |
+
"content": "<tool_call>",
|
| 118 |
+
"lstrip": false,
|
| 119 |
+
"normalized": false,
|
| 120 |
+
"rstrip": false,
|
| 121 |
+
"single_word": false,
|
| 122 |
+
"special": false
|
| 123 |
+
},
|
| 124 |
+
"248059": {
|
| 125 |
+
"content": "</tool_call>",
|
| 126 |
+
"lstrip": false,
|
| 127 |
+
"normalized": false,
|
| 128 |
+
"rstrip": false,
|
| 129 |
+
"single_word": false,
|
| 130 |
+
"special": false
|
| 131 |
+
},
|
| 132 |
+
"248060": {
|
| 133 |
+
"content": "<|fim_prefix|>",
|
| 134 |
+
"lstrip": false,
|
| 135 |
+
"normalized": false,
|
| 136 |
+
"rstrip": false,
|
| 137 |
+
"single_word": false,
|
| 138 |
+
"special": false
|
| 139 |
+
},
|
| 140 |
+
"248061": {
|
| 141 |
+
"content": "<|fim_middle|>",
|
| 142 |
+
"lstrip": false,
|
| 143 |
+
"normalized": false,
|
| 144 |
+
"rstrip": false,
|
| 145 |
+
"single_word": false,
|
| 146 |
+
"special": false
|
| 147 |
+
},
|
| 148 |
+
"248062": {
|
| 149 |
+
"content": "<|fim_suffix|>",
|
| 150 |
+
"lstrip": false,
|
| 151 |
+
"normalized": false,
|
| 152 |
+
"rstrip": false,
|
| 153 |
+
"single_word": false,
|
| 154 |
+
"special": false
|
| 155 |
+
},
|
| 156 |
+
"248063": {
|
| 157 |
+
"content": "<|fim_pad|>",
|
| 158 |
+
"lstrip": false,
|
| 159 |
+
"normalized": false,
|
| 160 |
+
"rstrip": false,
|
| 161 |
+
"single_word": false,
|
| 162 |
+
"special": false
|
| 163 |
+
},
|
| 164 |
+
"248064": {
|
| 165 |
+
"content": "<|repo_name|>",
|
| 166 |
+
"lstrip": false,
|
| 167 |
+
"normalized": false,
|
| 168 |
+
"rstrip": false,
|
| 169 |
+
"single_word": false,
|
| 170 |
+
"special": false
|
| 171 |
+
},
|
| 172 |
+
"248065": {
|
| 173 |
+
"content": "<|file_sep|>",
|
| 174 |
+
"lstrip": false,
|
| 175 |
+
"normalized": false,
|
| 176 |
+
"rstrip": false,
|
| 177 |
+
"single_word": false,
|
| 178 |
+
"special": false
|
| 179 |
+
},
|
| 180 |
+
"248066": {
|
| 181 |
+
"content": "<tool_response>",
|
| 182 |
+
"lstrip": false,
|
| 183 |
+
"normalized": false,
|
| 184 |
+
"rstrip": false,
|
| 185 |
+
"single_word": false,
|
| 186 |
+
"special": false
|
| 187 |
+
},
|
| 188 |
+
"248067": {
|
| 189 |
+
"content": "</tool_response>",
|
| 190 |
+
"lstrip": false,
|
| 191 |
+
"normalized": false,
|
| 192 |
+
"rstrip": false,
|
| 193 |
+
"single_word": false,
|
| 194 |
+
"special": false
|
| 195 |
+
},
|
| 196 |
+
"248068": {
|
| 197 |
+
"content": "<think>",
|
| 198 |
+
"lstrip": false,
|
| 199 |
+
"normalized": false,
|
| 200 |
+
"rstrip": false,
|
| 201 |
+
"single_word": false,
|
| 202 |
+
"special": false
|
| 203 |
+
},
|
| 204 |
+
"248069": {
|
| 205 |
+
"content": "</think>",
|
| 206 |
+
"lstrip": false,
|
| 207 |
+
"normalized": false,
|
| 208 |
+
"rstrip": false,
|
| 209 |
+
"single_word": false,
|
| 210 |
+
"special": false
|
| 211 |
+
},
|
| 212 |
+
"248070": {
|
| 213 |
+
"content": "<|audio_start|>",
|
| 214 |
+
"lstrip": false,
|
| 215 |
+
"normalized": false,
|
| 216 |
+
"rstrip": false,
|
| 217 |
+
"single_word": false,
|
| 218 |
+
"special": true
|
| 219 |
+
},
|
| 220 |
+
"248071": {
|
| 221 |
+
"content": "<|audio_end|>",
|
| 222 |
+
"lstrip": false,
|
| 223 |
+
"normalized": false,
|
| 224 |
+
"rstrip": false,
|
| 225 |
+
"single_word": false,
|
| 226 |
+
"special": true
|
| 227 |
+
},
|
| 228 |
+
"248072": {
|
| 229 |
+
"content": "<tts_pad>",
|
| 230 |
+
"lstrip": false,
|
| 231 |
+
"normalized": false,
|
| 232 |
+
"rstrip": false,
|
| 233 |
+
"single_word": false,
|
| 234 |
+
"special": true
|
| 235 |
+
},
|
| 236 |
+
"248073": {
|
| 237 |
+
"content": "<tts_text_bos>",
|
| 238 |
+
"lstrip": false,
|
| 239 |
+
"normalized": false,
|
| 240 |
+
"rstrip": false,
|
| 241 |
+
"single_word": false,
|
| 242 |
+
"special": true
|
| 243 |
+
},
|
| 244 |
+
"248074": {
|
| 245 |
+
"content": "<tts_text_eod>",
|
| 246 |
+
"lstrip": false,
|
| 247 |
+
"normalized": false,
|
| 248 |
+
"rstrip": false,
|
| 249 |
+
"single_word": false,
|
| 250 |
+
"special": true
|
| 251 |
+
},
|
| 252 |
+
"248075": {
|
| 253 |
+
"content": "<tts_text_bos_single>",
|
| 254 |
+
"lstrip": false,
|
| 255 |
+
"normalized": false,
|
| 256 |
+
"rstrip": false,
|
| 257 |
+
"single_word": false,
|
| 258 |
+
"special": true
|
| 259 |
+
},
|
| 260 |
+
"248076": {
|
| 261 |
+
"content": "<|audio_pad|>",
|
| 262 |
+
"lstrip": false,
|
| 263 |
+
"normalized": false,
|
| 264 |
+
"rstrip": false,
|
| 265 |
+
"single_word": false,
|
| 266 |
+
"special": true
|
| 267 |
+
}
|
| 268 |
+
},
|
| 269 |
+
"additional_special_tokens": [
|
| 270 |
+
"<|im_start|>",
|
| 271 |
+
"<|im_end|>",
|
| 272 |
+
"<|object_ref_start|>",
|
| 273 |
+
"<|object_ref_end|>",
|
| 274 |
+
"<|box_start|>",
|
| 275 |
+
"<|box_end|>",
|
| 276 |
+
"<|quad_start|>",
|
| 277 |
+
"<|quad_end|>",
|
| 278 |
+
"<|vision_start|>",
|
| 279 |
+
"<|vision_end|>",
|
| 280 |
+
"<|vision_pad|>",
|
| 281 |
+
"<|image_pad|>",
|
| 282 |
+
"<|video_pad|>"
|
| 283 |
+
],
|
| 284 |
+
"bos_token": null,
|
| 285 |
+
"chat_template": "{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- macro render_content(content, do_vision_count, is_system_content=false) %}\n {%- if content is string %}\n {{- content }}\n {%- elif content is iterable and content is not mapping %}\n {%- for item in content %}\n {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}\n {%- if is_system_content %}\n {{- raise_exception('System message cannot contain images.') }}\n {%- endif %}\n {%- if do_vision_count %}\n {%- set image_count.value = image_count.value + 1 %}\n {%- endif %}\n {%- if add_vision_id %}\n {{- 'Picture ' ~ image_count.value ~ ': ' }}\n {%- endif %}\n {{- '<|vision_start|><|image_pad|><|vision_end|>' }}\n {%- elif 'video' in item or item.type == 'video' %}\n {%- if is_system_content %}\n {{- raise_exception('System message cannot contain videos.') }}\n {%- endif %}\n {%- if do_vision_count %}\n {%- set video_count.value = video_count.value + 1 %}\n {%- endif %}\n {%- if add_vision_id %}\n {{- 'Video ' ~ video_count.value ~ ': ' }}\n {%- endif %}\n {{- '<|vision_start|><|video_pad|><|vision_end|>' }}\n {%- elif 'text' in item %}\n {{- item.text }}\n {%- else %}\n {{- raise_exception('Unexpected item type in content.') }}\n {%- endif %}\n {%- endfor %}\n {%- elif content is none or content is undefined %}\n {{- '' }}\n {%- else %}\n {{- raise_exception('Unexpected content type.') }}\n {%- endif %}\n{%- endmacro %}\n{%- if not messages %}\n {{- raise_exception('No messages provided.') }}\n{%- endif %}\n{%- if tools and tools is iterable and tools is not mapping %}\n {{- '<|im_start|>system\\n' }}\n {{- \"# Tools\\n\\nYou have access to the following functions:\\n\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\" }}\n {{- '\\n\\nIf you choose to call a function ONLY reply in the following format with NO suffix:\\n\\n<tool_call>\\n<function=example_function_name>\\n<parameter=example_parameter_1>\\nvalue_1\\n</parameter>\\n<parameter=example_parameter_2>\\nThis is the value for the second parameter\\nthat can span\\nmultiple lines\\n</parameter>\\n</function>\\n</tool_call>\\n\\n<IMPORTANT>\\nReminder:\\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\\n- Required parameters MUST be specified\\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\\n</IMPORTANT>' }}\n {%- if messages[0].role == 'system' %}\n {%- set content = render_content(messages[0].content, false, true)|trim %}\n {%- if content %}\n {{- '\\n\\n' + content }}\n {%- endif %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n{%- else %}\n {%- if messages[0].role == 'system' %}\n {%- set content = render_content(messages[0].content, false, true)|trim %}\n {{- '<|im_start|>system\\n' + content + '<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n {%- set index = (messages|length - 1) - loop.index0 %}\n {%- if ns.multi_step_tool and message.role == \"user\" %}\n {%- set content = render_content(message.content, false)|trim %}\n {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}\n {%- set ns.multi_step_tool = false %}\n {%- set ns.last_query_index = index %}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if ns.multi_step_tool %}\n {{- raise_exception('No user query found in messages.') }}\n{%- endif %}\n{%- for message in messages %}\n {%- set content = render_content(message.content, true)|trim %}\n {%- if message.role == \"system\" %}\n {%- if not loop.first %}\n {{- raise_exception('System message must be at the beginning.') }}\n {%- endif %}\n {%- elif message.role == \"user\" %}\n {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {%- set reasoning_content = '' %}\n {%- if message.reasoning_content is string %}\n {%- set reasoning_content = message.reasoning_content %}\n {%- else %}\n {%- if '</think>' in content %}\n {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n {%- endif %}\n {%- endif %}\n {%- set reasoning_content = reasoning_content|trim %}\n {%- if loop.index0 > ns.last_query_index %}\n {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content + '\\n</think>\\n\\n' + content }}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {%- if loop.first %}\n {%- if content|trim %}\n {{- '\\n\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n {%- else %}\n {{- '<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n {%- endif %}\n {%- else %}\n {{- '\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n {%- endif %}\n {%- if tool_call.arguments is defined %}\n {%- for args_name, args_value in tool_call.arguments|items %}\n {{- '<parameter=' + args_name + '>\\n' }}\n {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}\n {{- args_value }}\n {{- '\\n</parameter>\\n' }}\n {%- endfor %}\n {%- endif %}\n {{- '</function>\\n</tool_call>' }}\n {%- endfor %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- content }}\n {{- '\\n</tool_response>' }}\n {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n {{- '<|im_end|>\\n' }}\n {%- elif loop.last %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- else %}\n {{- raise_exception('Unexpected message role.') }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n {%- if enable_thinking is defined and enable_thinking is false %}\n {{- '<think>\\n\\n</think>\\n\\n' }}\n {%- else %}\n {{- '<think>\\n' }}\n {%- endif %}\n{%- endif %}",
|
| 286 |
+
"clean_up_tokenization_spaces": false,
|
| 287 |
+
"eos_token": "<|im_end|>",
|
| 288 |
+
"errors": "replace",
|
| 289 |
+
"model_max_length": 262144,
|
| 290 |
+
"pad_token": "<|endoftext|>",
|
| 291 |
+
"split_special_tokens": false,
|
| 292 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 293 |
+
"unk_token": null,
|
| 294 |
+
"add_bos_token": false,
|
| 295 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 296 |
+
"extra_special_tokens": {
|
| 297 |
+
"audio_bos_token": "<|audio_start|>",
|
| 298 |
+
"audio_eos_token": "<|audio_end|>",
|
| 299 |
+
"audio_token": "<|audio_pad|>",
|
| 300 |
+
"image_token": "<|image_pad|>",
|
| 301 |
+
"video_token": "<|video_pad|>",
|
| 302 |
+
"vision_bos_token": "<|vision_start|>",
|
| 303 |
+
"vision_eos_token": "<|vision_end|>"
|
| 304 |
+
}
|
| 305 |
+
}
|
vocab.json
ADDED
|
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See raw diff
|
|
|