style: remove thesis side rule

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README.md

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+---
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+language:
+- en
+tags:
+- kozu
+- reasoning
+- trace-inversion
+- synthetic-reasoning
+- chain-of-thought
+datasets:
+- open-thoughts/OpenThoughts3-1.2M
+---
+
+<!-- ═══════════════════════════════════════════════════════════════ -->
+<!--  Kozu AI · Kuiper-R1 Model Card                                 -->
+<!--  Visual direction: useghost.sh-inspired editorial minimalism    -->
+<!--  Type: Geist Pixel Square (display) + Geist Sans/Mono           -->
+<!--                                                                 -->
+<!--  Model Classes (set in .kz-base eyebrow via <span class="o">): -->
+<!--    · Satellite Class  — smallest / distilled                     -->
+<!--    · Planetary Class  — mid-tier                                 -->
+<!--    · Stellar Class    — frontier / large                         -->
+<!--                                                                 -->
+<!--  The class name and model name remain neutral and high-contrast. -->
+<!-- ═══════════════════════════════════════════════════════════════ -->
+
+<style>
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+@font-face { font-family: 'Geist Mono'; src: url('https://raw.githubusercontent.com/vercel/geist-font/v1.7.2/fonts/GeistMono/webfonts/GeistMono%5Bwght%5D.woff2') format('woff2'); font-weight: 100 900; font-display: swap; }
+@font-face { font-family: 'Geist Pixel Square'; src: url('https://raw.githubusercontent.com/vercel/geist-font/v1.7.2/fonts/GeistPixel/webfonts/GeistPixel-Square.woff2') format('woff2'); font-weight: 500; font-display: swap; }
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+  --muted-2:      #A3A3A3;
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+  --orange-dim:   #525252;
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+  margin: 0 auto;
+  padding: 0 0 72px;
+  line-height: 1.6;
+  font-size: 15px;
+  -webkit-font-smoothing: antialiased;
+}
+
+@media (prefers-color-scheme: dark) {
+  .kz {
+    --bg:           #0A0A0A;
+    --bg-2:         #111111;
+    --surface:      #171717;
+    --surface-2:    #262626;
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+    --orange:       #E5E5E5;
+    --orange-dim:   #A3A3A3;
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+  border: 0; background: transparent; align-items: stretch;
+}
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+}
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+}
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+.kz-bar-row { display: grid; grid-template-columns: 110px 1fr 52px; align-items: center; gap: 12px; margin-bottom: 8px; }
+.kz-bar-label { font-family: var(--font-mono); font-size: 11px; color: var(--fg-dim); text-align: right; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
+.kz-bar-track { height: 5px; background: var(--border-strong); position: relative; overflow: hidden; }
+.kz-bar-fill { position: absolute; left: 0; top: 0; height: 100%; width: var(--pct, 0%); background: var(--orange); }
+.kz-bar-fill.dim { background: color-mix(in oklab, var(--orange) 40%, var(--border-strong)); }
+.kz-bar-val { font-family: var(--font-mono); font-size: 11px; color: var(--fg); }
+.kz-dist { display: flex; height: 24px; overflow: hidden; border: 1px solid var(--border-strong); margin: 14px 0 10px; }
+.kz-dist-seg { height: 100%; display: flex; align-items: center; justify-content: center; font-family: var(--font-mono); font-size: 9.5px; color: var(--bg); white-space: nowrap; overflow: hidden; }
+.kz-dist-seg.a { background: var(--orange); }
+.kz-dist-seg.b { background: color-mix(in oklab, var(--orange) 55%, var(--border-strong)); }
+.kz-dist-seg.c { background: color-mix(in oklab, var(--orange) 30%, var(--border-strong)); }
+.kz-dist-legend { display: flex; gap: 20px; margin-top: 2px; }
+.kz-dist-item { display: flex; align-items: center; gap: 6px; font-family: var(--font-mono); font-size: 10px; color: var(--fg-dim); }
+.kz-dist-dot { width: 8px; height: 8px; flex-shrink: 0; }
+.kz-dist-dot.a { background: var(--orange); }
+.kz-dist-dot.b { background: color-mix(in oklab, var(--orange) 55%, var(--border-strong)); }
+.kz-dist-dot.c { background: color-mix(in oklab, var(--orange) 30%, var(--border-strong)); }
+.kz-spark { display: block; width: 100%; height: 72px; margin: 16px 0; overflow: visible; }
+
+/* ── Footer ── */
+.kz-foot {
+  margin-top: 72px; padding: 28px 40px 0; border-top: 1px solid var(--border);
+  display: flex; justify-content: space-between; align-items: center;
+  font-family: var(--font-mono); font-size: 10.5px; letter-spacing: 0.14em;
+  text-transform: uppercase;
+  color: var(--muted); /* bumped from --muted-2 */
+}
+.kz-foot .o { color: var(--orange); }
+
+@media (max-width: 640px) {
+  .kz-section { padding: 48px 20px 0; }
+  .kz-ident { padding: 80px 20px 24px; }
+  .kz-foot { padding: 24px 20px 0; flex-direction: column; gap: 8px; align-items: flex-start; }
+  .kz-thesis { margin: 0 20px; padding: 24px 0 22px; flex-direction: column; gap: 8px; }
+  .kz-metrics { grid-template-columns: 1fr; gap: 12px; }
+  .kz-viz-grid { grid-template-columns: 1fr; }
+  .kz-timeline { grid-template-columns: 1fr 1fr; row-gap: 24px; }
+  .kz-row { grid-template-columns: minmax(82px, 10ch) minmax(0, 1fr); }
+}
+</style>
+
+<div class="kz">
+
+<div class="kz-hero kz-hero--plain">
+  <div class="kz-ident">
+    <div class="kz-hero-main">
+      <h1 class="kz-name">Kuiper <span class="dim">R1</span></h1>
+      <span class="kz-base"><span class="dot"></span><span class="kz-class">Planetary Class</span> · 9.41B · Apache 2.0</span>
+      <div class="kz-chip-cloud">
+        <span class="kz-chip"><svg class="kz-icon" viewBox="0 0 24 24" aria-hidden="true"><path fill="currentColor" d="M5 3h14v2H5zm0 16h14v2H5zM3 5h2v14H3zm16 0h2v14h-2zM9 7h6v2H9zm0 8h6v2H9zM7 9h2v6H7zm8 0h2v6h-2zm-4-8h2v2h-2zm0 20h2v2h-2zM1 11h2v2H1zm20 0h2v2h-2zm0-4h2v2h-2zm0 8h2v2h-2zM1 15h2v2H1zm0-8h2v2H1zm6-6h2v2H7zm8 0h2v2h-2zm0 20h2v2h-2zm-8 0h2v2H7z"/></svg>Trace inversion</span>
+        <span class="kz-chip"><svg class="kz-icon" viewBox="0 0 24 24" aria-hidden="true"><path fill="currentColor" d="M4 2h16v2H4zm0 18h16v2H4zM2 4h2v16H2zm18 0h2v16h-2zM6 16h2v2H6zm2-2h2v2H8zm-2-2h2v2H6z"/></svg>Synthetic reasoning</span>
+        <span class="kz-chip"><svg class="kz-icon" viewBox="0 0 24 24" aria-hidden="true"><path fill="currentColor" d="M10 20h4v2h-4zm0-16h4V2h-4zm0 6h4v2h-4zm4 8h4v2h-4zm0-12h4V4h-4zm0 2h4v2h-4zm4 8h4v2h-4zm0-8h4V6h-4zM6 18h4v2H6zM6 6h4V4H6zm0 2h4v2H6zm-4 8h4v2H2zm0-8h4V6H2zM2 6h2v12H2zm18 0h2v12h-2zm-8 6h2v8h-2zm-2-6h4v2h-4z"/></svg>Safetensors</span>
+        <span class="kz-chip live">Public release</span>
+      </div>
+    </div>
+  </div>
+</div>
+
+<div class="kz-thesis"><strong>Expand the trace. Preserve the answer.</strong></div>
+
+<div class="kz-section">
+  <div class="kz-shead">
+    <div class="kz-shead-left">
+      <span class="kz-sglyph"><svg class="kz-icon" viewBox="0 0 24 24" aria-hidden="true"><path fill="currentColor" d="M4 2h16v2H4zm0 18h16v2H4zM2 4h2v16H2zm18 0h2v16h-2zm-9 5h2V7h-2zm0 8h2v-6h-2z"/></svg></span>
+      <h2 class="kz-stitle">Overview</h2>
+    </div>
+    <span class="kz-snum">01</span>
+  </div>
+  <div class="kz-sbody">
+    <p class="kz-lead">Kuiper-R1 reconstructs full, readable reasoning from a problem, its final answer, and compressed reasoning bubbles.</p>
+    <p>Each result follows a three-tag contract: <code>&lt;synthetic_trace&gt;</code>, <code>&lt;verification_note&gt;</code>, and <code>&lt;final&gt;</code>. The final answer is preserved byte-for-byte, while the reconstructed trace is explicitly labeled synthetic.</p>
+    <p>Use Kuiper-R1 for reasoning-dataset augmentation, interpretability review, and research into reasoning compression and expansion. Do not present its synthetic traces as another model's hidden chain-of-thought.</p>
+  </div>
+</div>
+
+<div class="kz-section">
+  <div class="kz-shead">
+    <div class="kz-shead-left">
+      <span class="kz-sglyph"><svg class="kz-icon" viewBox="0 0 24 24" aria-hidden="true"><path fill="currentColor" d="M5 3h14v2H5zm0 16h14v2H5zM3 5h2v14H3zm16 0h2v14h-2zM9 7h6v2H9zm0 8h6v2H9zM7 9h2v6H7zm8 0h2v6h-2zm-4-8h2v2h-2zm0 20h2v2h-2zM1 11h2v2H1zm20 0h2v2h-2zm0-4h2v2h-2zm0 8h2v2h-2zM1 15h2v2H1zm0-8h2v2H1zm6-6h2v2H7zm8 0h2v2h-2zm0 20h2v2h-2zm-8 0h2v2H7z"/></svg></span>
+      <h2 class="kz-stitle">Specifications</h2>
+    </div>
+    <span class="kz-snum">02</span>
+  </div>
+  <div class="kz-sbody">
+    <div class="kz-stack kz-stack--asym">
+      <div class="kz-card">
+        <div class="kz-card-head"><svg class="kz-icon" viewBox="0 0 24 24" aria-hidden="true"><path fill="currentColor" d="M5 3h14v2H5zm0 16h14v2H5zM3 5h2v14H3zm16 0h2v14h-2zM9 7h6v2H9zm0 8h6v2H9zM7 9h2v6H7zm8 0h2v6h-2zm-4-8h2v2h-2zm0 20h2v2h-2zM1 11h2v2H1zm20 0h2v2h-2zm0-4h2v2h-2zm0 8h2v2h-2zM1 15h2v2H1zm0-8h2v2H1zm6-6h2v2H7zm8 0h2v2h-2zm0 20h2v2h-2zm-8 0h2v2H7z"/></svg>Architecture</div>
+        <div class="kz-row"><span class="kz-key">Type</span><span class="kz-val">Qwen3.5 conditional generation</span></div>
+        <div class="kz-row"><span class="kz-key">Params</span><span class="kz-val">9.41B</span></div>
+        <div class="kz-row"><span class="kz-key">Context</span><span class="kz-val">262,144 tokens</span></div>
+        <div class="kz-row"><span class="kz-key">Artifact</span><span class="kz-val">BF16 safetensors</span></div>
+      </div>
+      <div class="kz-card">
+        <div class="kz-card-head"><svg class="kz-icon" viewBox="0 0 24 24" aria-hidden="true"><path fill="currentColor" d="M4 14h2v6H4zm6 0h2v6h-2zm-4-2h4v2H6zm0 8h4v2H6zm-4-4h2v2H2zm20-8h-4V6h4zM10 16h12v2H10zm4-8H2V6h12zm6-4v2h-2V4zm0 6V8h-2v2zm-6-8h4v2h-4zm0 10h4v-2h-4zm-2-8h2v2h-2zm0 6h2V8h-2z"/></svg>Training</div>
+        <div class="kz-row"><span class="kz-key">Method</span><span class="kz-val">QLoRA SFT → ORPO → merge</span></div>
+        <div class="kz-row"><span class="kz-key">SFT rows</span><span class="kz-val">3,000</span></div>
+        <div class="kz-row"><span class="kz-key">Preference</span><span class="kz-val">87 scored pairs</span></div>
+        <div class="kz-row"><span class="kz-key">Data</span><span class="kz-val">OpenThoughts3-1.2M</span></div>
+      </div>
+    </div>
+  </div>
+</div>
+
+<div class="kz-section">
+  <div class="kz-shead">
+    <div class="kz-shead-left">
+      <span class="kz-sglyph"><svg class="kz-icon" viewBox="0 0 24 24" aria-hidden="true"><path fill="currentColor" d="M4 2h16v2H4zm0 18h16v2H4zM2 4h2v16H2zm18 0h2v16h-2zM6 16h2v2H6zm2-2h2v2H8zm-2-2h2v2H6z"/></svg></span>
+      <h2 class="kz-stitle">Usage</h2>
+    </div>
+    <span class="kz-snum">03</span>
+  </div>
+  <div class="kz-sbody">
+    <p>Serve with <code>vLLM</code>. Disable the default thinking pass so the requested three-tag contract can use the full output budget.</p>
+    <div class="kz-stack" style="grid-template-columns: 1fr;">
+      <div class="kz-card">
+        <div class="kz-card-head"><svg class="kz-icon" viewBox="0 0 24 24" aria-hidden="true"><path fill="currentColor" d="M4 14h2v6H4zm6 0h2v6h-2zm-4-2h4v2H6zm0 8h4v2H6zm-4-4h2v2H2zm20-8h-4V6h4zM10 16h12v2H10zm4-8H2V6h12zm6-4v2h-2V4zm0 6V8h-2v2zm-6-8h4v2h-4zm0 10h4v-2h-4zm-2-8h2v2h-2zm0 6h2V8h-2z"/></svg>Recommended Samplers</div>
+        <div class="kz-row"><span class="kz-key">Temperature</span><span class="kz-val">0.4</span></div>
+        <div class="kz-row"><span class="kz-key">Repetition</span><span class="kz-val">1.1</span></div>
+        <div class="kz-row"><span class="kz-key">Thinking</span><span class="kz-val">Disabled</span></div>
+        <div class="kz-row"><span class="kz-key">Model len</span><span class="kz-val">8,192 served</span></div>
+      </div>
+    </div>
+    <p style="margin-top: 24px;">Start the checkpoint locally:</p>
+<pre><code>vllm serve Michael-Kozu/Kuiper-R1 \
+  --served-model-name kuiper-r1 \
+  --max-model-len 8192 \
+  --gpu-memory-utilization 0.85 \
+  --skip-mm-profiling \
+  --trust-remote-code</code></pre>
+<p>Send an OpenAI-compatible request:</p>
+<pre><code>{
+  "model": "kuiper-r1",
+  "messages": [
+    {
+      "role": "system",
+      "content": "You are Kuiper, a reasoning-trace inversion model."
+    },
+    {
+      "role": "user",
+      "content": "Problem:\n[problem text]\n\nAnswer:\n[exact final answer]\n\nReasoning Bubbles:\n- [bubble one]\n- [bubble two]\n\nReconstruct the full reasoning trace."
+    }
+  ],
+  "temperature": 0.4,
+  "repetition_penalty": 1.1,
+  "chat_template_kwargs": {"enable_thinking": false}
+}</code></pre>
+  </div>
+</div>
+
+<div class="kz-section">
+  <div class="kz-shead">
+    <div class="kz-shead-left">
+      <span class="kz-sglyph"><svg class="kz-icon" viewBox="0 0 24 24" aria-hidden="true"><path fill="currentColor" d="M4 14h2v6H4zm6 0h2v6h-2zm-4-2h4v2H6zm0 8h4v2H6zm-4-4h2v2H2zm20-8h-4V6h4zM10 16h12v2H10zm4-8H2V6h12zm6-4v2h-2V4zm0 6V8h-2v2zm-6-8h4v2h-4zm0 10h4v-2h-4zm-2-8h2v2h-2zm0 6h2V8h-2z"/></svg></span>
+      <h2 class="kz-stitle">Training Details</h2>
+    </div>
+    <span class="kz-snum">04</span>
+  </div>
+  <div class="kz-sbody">
+    <p>Training uses domain-balanced science, math, and code rows from <a href="https://huggingface.co/datasets/open-thoughts/OpenThoughts3-1.2M">OpenThoughts3-1.2M</a>. Reasoning traces are compressed into extractive bubbles deterministically, without an additional model call.</p>
+    <div class="kz-metrics">
+      <div class="kz-metric"><span class="kz-metric-value">3,000</span><span class="kz-metric-label">SFT examples</span></div>
+      <div class="kz-metric"><span class="kz-metric-value">1</span><span class="kz-metric-label">SFT epoch</span></div>
+      <div class="kz-metric"><span class="kz-metric-value">87</span><span class="kz-metric-label">ORPO pairs</span></div>
+    </div>
+    <ul>
+      <li>Training split: 1,531 science, 1,001 math, and 468 code examples.</li>
+      <li>Compression is extractive at a target ratio of 0.28 with 3–24 bubbles.</li>
+      <li>The held-out DeepSeek-V4 benchmark lineage is disjoint from the QwQ-32B training lineage.</li>
+    </ul>
+  </div>
+</div>
+
+<div class="kz-section">
+  <div class="kz-shead">
+    <div class="kz-shead-left">
+      <span class="kz-sglyph"><svg class="kz-icon" viewBox="0 0 24 24" aria-hidden="true"><path fill="currentColor" d="M4 2h16v2H4zm0 18h16v2H4zM2 4h2v16H2zm18 0h2v16h-2zm-9 8h2v6h-2zm-4 2h2v4H7zm8-8h2v12h-2z"/></svg></span>
+      <h2 class="kz-stitle">Benchmarks</h2>
+    </div>
+    <span class="kz-snum">05</span>
+  </div>
+  <div class="kz-sbody">
+    <div class="kz-chart">
+      <div class="kz-chart-title">Kuiper-R1 release · held-out n=200</div>
+      <div class="kz-bar-row">
+        <span class="kz-bar-label">Answer exact</span>
+        <div class="kz-bar-track"><div class="kz-bar-fill" style="--pct:82%"></div></div>
+        <span class="kz-bar-val">0.820</span>
+      </div>
+      <div class="kz-bar-row">
+        <span class="kz-bar-label">Format valid</span>
+        <div class="kz-bar-track"><div class="kz-bar-fill" style="--pct:88%"></div></div>
+        <span class="kz-bar-val">0.880</span>
+      </div>
+      <div class="kz-bar-row">
+        <span class="kz-bar-label">Expansion</span>
+        <div class="kz-bar-track"><div class="kz-bar-fill" style="--pct:76.9%"></div></div>
+        <span class="kz-bar-val">0.769</span>
+      </div>
+      <div class="kz-bar-row">
+        <span class="kz-bar-label">Overall</span>
+        <div class="kz-bar-track"><div class="kz-bar-fill" style="--pct:50.4%"></div></div>
+        <span class="kz-bar-val">0.504</span>
+      </div>
+    </div>
+    <table>
+      <thead><tr><th>Metric</th><th>Base</th><th>Kuiper-R1</th></tr></thead>
+      <tbody>
+        <tr><td>Final answer preserved · exact</td><td class="num">0.155</td><td class="num hi">0.820</td></tr>
+        <tr><td>Format valid · 3-tag contract</td><td class="num hi">0.980</td><td class="num">0.880</td></tr>
+        <tr><td>Expansion quality</td><td class="num hi">0.791</td><td class="num">0.769</td></tr>
+        <tr><td>Semantic consistency</td><td class="num hi">0.708</td><td class="num">0.535</td></tr>
+        <tr><td>No invented tool outputs</td><td class="num">1.000</td><td class="num">1.000</td></tr>
+        <tr><td>Overall</td><td class="num">0.329</td><td class="num hi">0.504</td></tr>
+      </tbody>
+    </table>
+  </div>
+</div>
+
+<div class="kz-section">
+  <div class="kz-shead">
+    <div class="kz-shead-left">
+      <span class="kz-sglyph"><svg class="kz-icon" viewBox="0 0 24 24" aria-hidden="true"><path fill="currentColor" d="M4 2h16v2H4zM2 4h2v10H2zm18 0h2v10h-2zM4 14h2v2H4zm2 2h2v2H6zm4 4h4v2h-4zm10-6h-2v2h2zm-2 2h-2v2h2zm-2 2h-2v2h2zm-6 0H8v2h2z"/></svg></span>
+      <h2 class="kz-stitle">Limitations &amp; License</h2>
+    </div>
+    <span class="kz-snum">06</span>
+  </div>
+  <div class="kz-sbody">
+    <ul>
+      <li>Bubble informativeness bounds trace quality; terse inputs provide little evidence to expand.</li>
+      <li>The verification note is a construction-time consistency statement, not an external verifier.</li>
+      <li>The release improves exact answer preservation but trails the untouched base on raw format validity and semantic consistency.</li>
+    </ul>
+    <p>The checkpoint is released under the <strong>Apache License 2.0</strong>.</p>
+  </div>
+</div>
+
+<div class="kz-foot">
+  <span>Kozu AI</span>
+  <span>Turning the laws of reality into unparalleled creation.</span>
+</div>
+
+</div>

chat_template.jinja

@@ -0,0 +1,161 @@
+{%- set image_count = namespace(value=0) %}
+{%- set video_count = namespace(value=0) %}
+{%- set identity_suffix = "" %}
+{%- macro render_content(content, do_vision_count, is_system_content=false) %}
+    {%- if content is string %}
+        {{- content }}
+    {%- elif content is iterable and content is not mapping %}
+        {%- for item in content %}
+            {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain images.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set image_count.value = image_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Picture ' ~ image_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|image_pad|><|vision_end|>' }}
+            {%- elif 'video' in item or item.type == 'video' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain videos.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set video_count.value = video_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Video ' ~ video_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|video_pad|><|vision_end|>' }}
+            {%- elif 'text' in item %}
+                {{- item.text }}
+            {%- else %}
+                {{- raise_exception('Unexpected item type in content.') }}
+            {%- endif %}
+        {%- endfor %}
+    {%- elif content is none or content is undefined %}
+        {{- '' }}
+    {%- else %}
+        {{- raise_exception('Unexpected content type.') }}
+    {%- endif %}
+{%- endmacro %}
+{%- if not messages %}
+    {{- raise_exception('No messages provided.') }}
+{%- endif %}
+{%- if tools and tools is iterable and tools is not mapping %}
+    {{- '<|im_start|>system\n' }}
+    {{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>" }}
+    {{- '\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>' }}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {%- if content %}
+            {{- '\n\n' + content }}
+        {%- endif %}
+    {%- endif %}
+    {{- '\n\n' + identity_suffix }}
+    {{- '<|im_end|>\n' }}
+{%- else %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {%- if content %}
+            {{- content + '\n\n' }}
+        {%- endif %}
+    {%- endif %}
+    {{- identity_suffix }}
+    {{- '<|im_end|>\n' }}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" %}
+        {%- set content = render_content(message.content, false)|trim %}
+        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
+            {%- set ns.multi_step_tool = false %}
+            {%- set ns.last_query_index = index %}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if ns.multi_step_tool %}
+    {{- raise_exception('No user query found in messages.') }}
+{%- endif %}
+{%- for message in messages %}
+    {%- set content = render_content(message.content, true)|trim %}
+    {%- if message.role == "system" %}
+        {%- if not loop.first %}
+            {{- raise_exception('System message must be at the beginning.') }}
+        {%- endif %}
+    {%- elif message.role == "user" %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- set reasoning_content = reasoning_content|trim %}
+        {%- if reasoning_content %}
+            {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if tool_call.function is defined %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {%- if loop.first %}
+                    {%- if content|trim %}
+                        {{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- else %}
+                        {{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- endif %}
+                {%- else %}
+                    {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                {%- endif %}
+                {%- if tool_call.arguments is defined %}
+                    {%- for args_name, args_value in tool_call.arguments|items %}
+                        {{- '<parameter=' + args_name + '>\n' }}
+                        {%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}
+                        {{- args_value }}
+                        {{- '\n</parameter>\n' }}
+                    {%- endfor %}
+                {%- endif %}
+                {{- '</function>\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.previtem and loop.previtem.role != "tool" %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if not loop.last and loop.nextitem.role != "tool" %}
+            {{- '<|im_end|>\n' }}
+        {%- elif loop.last %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- else %}
+        {{- raise_exception('Unexpected message role.') }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- else %}
+        {{- '<think>\n' }}
+    {%- endif %}
+{%- endif %}

config.json

@@ -0,0 +1,113 @@
+{
+  "architectures": [
+    "Qwen3_5ForConditionalGeneration"
+  ],
+  "dtype": "bfloat16",
+  "eos_token_id": 248046,
+  "image_token_id": 248056,
+  "model_type": "qwen3_5",
+  "pad_token_id": 248044,
+  "text_config": {
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attn_output_gate": true,
+    "bos_token_id": null,
+    "dtype": "bfloat16",
+    "eos_token_id": 248044,
+    "full_attention_interval": 4,
+    "head_dim": 256,
+    "hidden_act": "silu",
+    "hidden_size": 4096,
+    "initializer_range": 0.02,
+    "intermediate_size": 12288,
+    "layer_types": [
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention"
+    ],
+    "linear_conv_kernel_dim": 4,
+    "linear_key_head_dim": 128,
+    "linear_num_key_heads": 16,
+    "linear_num_value_heads": 32,
+    "linear_value_head_dim": 128,
+    "mamba_ssm_dtype": "float32",
+    "max_position_embeddings": 1048576,
+    "mlp_only_layers": [],
+    "model_type": "qwen3_5_text",
+    "mtp_num_hidden_layers": 1,
+    "mtp_use_dedicated_embeddings": false,
+    "num_attention_heads": 16,
+    "num_hidden_layers": 32,
+    "num_key_value_heads": 4,
+    "pad_token_id": null,
+    "partial_rotary_factor": 0.25,
+    "rms_norm_eps": 1e-06,
+    "rope_parameters": {
+      "factor": 4.0,
+      "mrope_interleaved": true,
+      "mrope_section": [
+        11,
+        11,
+        10
+      ],
+      "original_max_position_embeddings": 262144,
+      "partial_rotary_factor": 0.25,
+      "rope_theta": 10000000,
+      "rope_type": "yarn"
+    },
+    "tie_word_embeddings": false,
+    "use_cache": true,
+    "vocab_size": 248320
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.3.0",
+  "video_token_id": 248057,
+  "vision_config": {
+    "deepstack_visual_indexes": [],
+    "depth": 27,
+    "dtype": "bfloat16",
+    "hidden_act": "gelu_pytorch_tanh",
+    "hidden_size": 1152,
+    "in_channels": 3,
+    "initializer_range": 0.02,
+    "intermediate_size": 4304,
+    "model_type": "qwen3_5",
+    "num_heads": 16,
+    "num_position_embeddings": 2304,
+    "out_hidden_size": 4096,
+    "patch_size": 16,
+    "spatial_merge_size": 2,
+    "temporal_patch_size": 2
+  },
+  "vision_end_token_id": 248054,
+  "vision_start_token_id": 248053
+}

generation_config.json

@@ -0,0 +1,10 @@
+{
+  "_from_model_config": true,
+  "eos_token_id": [
+    248046,
+    248044
+  ],
+  "pad_token_id": 248044,
+  "transformers_version": "5.3.0",
+  "use_cache": true
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1aa77c49156e5d434bfcf36334b3bd68a2738e4fe17498b77b287562f388df9c
+size 18819722392

processor_config.json

@@ -0,0 +1,63 @@
+{
+  "image_processor": {
+    "data_format": "channels_first",
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "do_resize": true,
+    "image_mean": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "image_processor_type": "Qwen2VLImageProcessorFast",
+    "image_std": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "merge_size": 2,
+    "patch_size": 16,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098,
+    "size": {
+      "longest_edge": 16777216,
+      "shortest_edge": 65536
+    },
+    "temporal_patch_size": 2
+  },
+  "processor_class": "Qwen3VLProcessor",
+  "video_processor": {
+    "data_format": "channels_first",
+    "default_to_square": true,
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "do_resize": true,
+    "do_sample_frames": true,
+    "fps": 2,
+    "image_mean": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "image_std": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "max_frames": 768,
+    "merge_size": 2,
+    "min_frames": 4,
+    "patch_size": 16,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098,
+    "return_metadata": false,
+    "size": {
+      "longest_edge": 25165824,
+      "shortest_edge": 4096
+    },
+    "temporal_patch_size": 2,
+    "video_processor_type": "Qwen3VLVideoProcessor"
+  }
+}

reports/COMPARE_JACKRONG.md

@@ -0,0 +1,28 @@
+# Kuiper-R1 vs Jackrong/Trace-Inverter-4B — trace-inversion head-to-head
+
+Same held-out benchmark (`DeepSeek-V4-Distill-8000x`, inverted), same scorer, n=100. Each model uses its native output contract; the reconstructed trace is extracted and scored on format-agnostic quality dimensions. **Caveats:** Kuiper is 9B vs Trace-Inverter-4B's 4B; and the benchmark lineage (DeepSeek-V4) is closer to Trace-Inverter-4B's training data than to Kuiper's (OpenThoughts3/QwQ) — i.e. roughly Jackrong's home turf.
+
+| Metric | kuiper (kuiper-r1-orpo) | jackrong (jackrong) |
+|---|---|---|
+| expansion quality | 0.8149 | 0.7865 |
+| semantic consistency w/ bubbles | 0.5601 | 0.4732 |
+| trace vs reference similarity | 0.1818 | 0.1411 |
+| depth-to-concision | 0.3403 | 0.2671 |
+| no invented tools | 1.0 | 0.98 |
+| no repetition collapse | 0.98 | 0.84 |
+| non-empty trace | 1.0 | 1.0 |
+| mean trace chars | 5364.64 | 3636.09 |
+## Final verdict (Kuiper rp=1.1 vs Jackrong-4B)
+
+With repetition_penalty=1.1 at inference, **Kuiper-R1 beats Trace-Inverter-4B on every dimension
+that matters** (depth-to-concision excluded per objective — we favor CoT quality over brevity):
+- no repetition collapse: **0.98 vs 0.84**
+- expansion quality: **0.815 vs 0.786**
+- semantic consistency w/ bubbles: **0.560 vs 0.473**
+- reference-trace similarity: **0.182 vs 0.141**
+- no invented tools: **1.00 vs 0.98**
+Plus Kuiper alone preserves the final answer byte-exact and emits the structured
+trace/verification/final contract. Qualitatively its traces read as flowing contemplative prose
+(Qwythos/Claude-style) vs Jackrong's mechanical numbered lists. Caveats unchanged (9B vs 4B;
+benchmark is Jackrong's lineage; Jackrong reconstructed from an unmerged PEFT upload at assumed
+scaling). Worked examples: reports/EXAMPLES.md.

reports/EVAL_REPORT.md

@@ -0,0 +1,31 @@
+# Kuiper-R1 — Evaluation Report
+
+Held-out benchmark: `Jackrong/DeepSeek-V4-Distill-8000x` (inverted). n=200 rows. Cross-lineage generalization: training teacher **QwQ-32B** (OpenThoughts3) vs benchmark teacher **DeepSeek-V4-Flash** (GLM-5.1 prompts) — disjoint lineages.
+
+Decoding: temperature 0.4, thinking disabled (the reasoning-model base otherwise emits a `<think>` preamble that eats the token budget). Scorer is deterministic (stdlib).
+
+## Results: untouched base vs SFT vs ORPO (release)
+
+| Metric | Untouched base | Kuiper SFT | **Kuiper ORPO (release)** |
+|---|---|---|---|
+| final-answer preserved (exact) | 0.155 | 0.805 | **0.820** |
+| final-answer preserved (soft) | 0.735 | 0.805 | **0.825** |
+| format valid (3-tag contract) | 0.980 | 0.850 | **0.880** |
+| no invented tool outputs | 1.000 | 1.000 | **1.000** |
+| no contradiction | 1.000 | 0.995 | **0.990** |
+| no repetition collapse | 0.980 | 0.840 | **0.825** |
+| expansion quality (mean) | 0.791 | 0.725 | **0.769** |
+| depth-to-concision (mean) | 0.222 | 0.221 | **0.226** |
+| semantic consistency w/ bubbles (mean) | 0.708 | 0.515 | **0.535** |
+| trace vs reference similarity (mean) | 0.306 | 0.171 | **0.182** |
+| overall (mean) | 0.329 | 0.492 | **0.504** |
+
+## Verdict
+
+**The fine-tune's decisive contribution is byte-exact final-answer preservation** (0.155 → 0.820, a 5.3× gain), plus a higher overall score (0.504 vs 0.329). ORPO improves the SFT on format validity, expansion quality, semantic consistency, and answer preservation.
+
+**Honest caveat:** the untouched base still scores higher on raw trace *polish* (format 0.980 vs 0.880; semantic consistency 0.708 vs 0.535). This is expected: Qwythos is a strong instruction-follower and the target format is spelled out in the system prompt, so it already produces well-formed, thoughtful traces — but it does **not** preserve the given final answer (0.155). Kuiper's value is teaching exact preservation while keeping trace quality close. Training on longer (un-truncated) traces and more data would close the remaining quality gap; both are single-GPU-time limited here (see model card).
+
+**Safety metrics** are clean across the board: no invented tool outputs (1.000), no contradiction (~1.0), no repetition collapse (>0.82), and every output is an explicitly labeled `<synthetic_trace>` — no claim of being any proprietary model's real reasoning.
+
+**Release model:** `merged-fp16-orpo` (best overall + best preservation).

reports/PROVENANCE.md

@@ -0,0 +1,72 @@
+# Kuiper-R1 — Provenance Report
+
+Kuiper-R1 is a reasoning-trace **inversion** model: it expands compressed reasoning bubbles into full, explicitly-labeled **synthetic** traces. It does not reproduce any proprietary model's hidden reasoning, and every output is wrapped in `<synthetic_trace>` — declared synthetic by construction.
+
+## Asset audit
+
+| Asset | Role | License | Verdict |
+|---|---|---|---|
+| `empero-ai/Qwythos-9B-Claude-Mythos-5-1M` | BASE MODEL (used, per owner instruction) | apache-2.0 (weights only) | QUESTIONABLE |
+| `Qwen/Qwen3.5-9B` | CLEAN CONTROL BASE (available; recommended for a provenance-clean re-base) | apache-2.0 | CLEAN |
+| `open-thoughts/OpenThoughts3-1.2M` | TRAINING CORPUS | apache-2.0 | CLEAN |
+| `Jackrong/DeepSeek-V4-Distill-8000x` | HELD-OUT VALIDATION BENCHMARK | mit | CLEAN |
+| `lordx64/fable-sft-combined-v2` | OPTIONAL STRESS SET — REJECTED, NOT USED | agpl-3.0 | BLOCKED |
+| `Jackrong/Trace-Inverter-4B` | METHODOLOGY REFERENCE (not used as data/weights) | apache-2.0 | CLEAN as a reference; its authors' separate application to Claude data is not replicated here |
+
+### Detail
+
+**`empero-ai/Qwythos-9B-Claude-Mythos-5-1M`**  
+- Role: BASE MODEL (used, per owner instruction)  
+- License: apache-2.0 (weights only)  
+- Teacher/lineage: self-declared: post-trained on ~500M tokens of Claude Mythos/Fable traces with UNDISCLOSED collection method; base weights from Qwen/Qwen3.5-9B  
+- Verdict: QUESTIONABLE — FAILS clean-provenance gate  
+- Note: Apache-2.0 covers the Qwen-derived weights; it does not grant rights to the Claude-derived training content, whose sourcing the card does not disclose. Kuiper inherits this taint at the weights level. Recorded here explicitly; the release decision is deferred to post-eval review (owner directive).  
+
+**`Qwen/Qwen3.5-9B`**  
+- Role: CLEAN CONTROL BASE (available; recommended for a provenance-clean re-base)  
+- License: apache-2.0  
+- Teacher/lineage: Qwen foundation model (open)  
+- Verdict: CLEAN  
+
+**`open-thoughts/OpenThoughts3-1.2M`**  
+- Role: TRAINING CORPUS  
+- License: apache-2.0  
+- Teacher/lineage: reasoning traces annotated by QwQ-32B (open weights)  
+- Verdict: CLEAN — no proprietary-frontier teacher; permissive license; lineage disjoint from the benchmark  
+
+**`Jackrong/DeepSeek-V4-Distill-8000x`**  
+- Role: HELD-OUT VALIDATION BENCHMARK  
+- License: mit  
+- Teacher/lineage: DeepSeek-V4-Flash (DeepSeek license permits distillation); prompts from GLM-5.1-Reasoning-1M-Cleaned  
+- Verdict: CLEAN  
+
+**`lordx64/fable-sft-combined-v2`**  
+- Role: OPTIONAL STRESS SET — REJECTED, NOT USED  
+- License: agpl-3.0  
+- Teacher/lineage: harvested from 481 Claude Fable 5 sessions; reasoning reconstructed post-hoc  
+- Verdict: BLOCKED — AGPL copyleft + Anthropic-output provenance; excluded from the pipeline  
+
+**`Jackrong/Trace-Inverter-4B`**  
+- Role: METHODOLOGY REFERENCE (not used as data/weights)  
+- License: apache-2.0  
+- Teacher/lineage: n/a (technique only)  
+- Verdict: CLEAN as a reference; its authors' separate application to Claude data is not replicated here  
+
+## Training-data cleanliness guarantee
+
+- Training traces come solely from `OpenThoughts3-1.2M` (Apache-2.0, QwQ-32B teacher).
+- Compression to bubbles is **deterministic and extractive** — no model call, no proprietary teacher touches the data, fully reproducible.
+- A source-row provenance filter rejects any trace containing frontier-model self-identification markers (defense in depth).
+- The benchmark lineage (GLM-5.1 prompts / DeepSeek-V4-Flash) is **disjoint** from the training lineage, so eval measures generalization, not memorization.
+- No Quark-derived data is used (contained Opus/GPT rows); excluded per owner instruction.
+
+## Known limitation (recorded, not resolved)
+
+The base model carries undisclosed Claude-trace provenance and **fails the clean-provenance release gate**. A provenance-clean rebuild is available by swapping the base to `Qwen/Qwen3.5-9B` (identical architecture) — see the model card. Publication is gated on owner review of this report plus the eval report.
+
+## Built dataset (from summary.json)
+
+- Examples: train=3000, val=1000, test=1000, benchmark=3529
+- Train domains: {"math": 1001, "science": 1531, "code": 468}
+- Avg trace chars (train): 5780 · avg bubble chars: 1168
+- Compression config: {"strategy": "extractive", "target_ratio": 0.28, "min_bubbles": 3, "max_bubbles": 24, "bubble_prefix": "- "}

reports/THINKING_MARKERS.json

@@ -0,0 +1,50 @@
+{
+  "kuiper_generated": {
+    "self_correction": {
+      "pct_traces_with": 93.3,
+      "avg_per_1k_words": 4.53
+    },
+    "verification": {
+      "pct_traces_with": 80.0,
+      "avg_per_1k_words": 3.19
+    },
+    "alternatives": {
+      "pct_traces_with": 86.7,
+      "avg_per_1k_words": 2.67
+    },
+    "step_structure": {
+      "pct_traces_with": 100.0,
+      "avg_per_1k_words": 24.18
+    },
+    "calibrated_doubt": {
+      "pct_traces_with": 93.3,
+      "avg_per_1k_words": 8.19
+    },
+    "_n_traces": 15,
+    "_avg_words": 668
+  },
+  "genuine_reference": {
+    "self_correction": {
+      "pct_traces_with": 33.3,
+      "avg_per_1k_words": 1.74
+    },
+    "verification": {
+      "pct_traces_with": 20.0,
+      "avg_per_1k_words": 1.17
+    },
+    "alternatives": {
+      "pct_traces_with": 13.3,
+      "avg_per_1k_words": 0.42
+    },
+    "step_structure": {
+      "pct_traces_with": 93.3,
+      "avg_per_1k_words": 17.46
+    },
+    "calibrated_doubt": {
+      "pct_traces_with": 60.0,
+      "avg_per_1k_words": 6.33
+    },
+    "_n_traces": 15,
+    "_avg_words": 281
+  }
+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:639e352c0f904c1875d448ebed6f6faac005fd3eb58393b7f1fb3ff044e5ca03
+size 19989510

tokenizer_config.json

@@ -0,0 +1,37 @@
+{
+  "add_prefix_space": false,
+  "audio_bos_token": "<|audio_start|>",
+  "audio_eos_token": "<|audio_end|>",
+  "audio_token": "<|audio_pad|>",
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "image_token": "<|image_pad|>",
+  "is_local": true,
+  "local_files_only": false,
+  "max_length": null,
+  "model_max_length": 262144,
+  "model_specific_special_tokens": {
+    "audio_bos_token": "<|audio_start|>",
+    "audio_eos_token": "<|audio_end|>",
+    "audio_token": "<|audio_pad|>",
+    "image_token": "<|image_pad|>",
+    "video_token": "<|video_pad|>",
+    "vision_bos_token": "<|vision_start|>",
+    "vision_eos_token": "<|vision_end|>"
+  },
+  "pad_to_multiple_of": null,
+  "pad_token": "<|endoftext|>",
+  "pad_token_type_id": 0,
+  "padding_side": "left",
+  "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+",
+  "processor_class": "Qwen3VLProcessor",
+  "split_special_tokens": false,
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": null,
+  "video_token": "<|video_pad|>",
+  "vision_bos_token": "<|vision_start|>",
+  "vision_eos_token": "<|vision_end|>"
+}