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jingyaogong 2026-04-20 16:55:17 +08:00
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<!-- Title Section -->
<div class="title-section">
<p class="tagline pixel-font">
Train a 67M Vision-Language Model from zero.<br/>
Train a 65M Vision-Language Model from zero.<br/>
2 hours. ¥2.6. One 3090.<br/>
See the World.
</p>
@ -537,7 +537,7 @@
<!-- Key Stats -->
<div class="stats-section">
<div class="stat-box">
<h3>67M</h3>
<h3>65M</h3>
<p>Parameters</p>
</div>
<div class="stat-box">
@ -598,13 +598,13 @@
<tbody>
<tr>
<td><strong>minimind-3v-moe</strong></td>
<td>202M-A67M</td>
<td>200M-A65M</td>
<td>1.0 GB</td>
<td>2026.04.20</td>
</tr>
<tr>
<td><strong>minimind-3v</strong></td>
<td>67M</td>
<td>65M</td>
<td>0.5 GB</td>
<td>2026.04.20</td>
</tr>
@ -634,9 +634,9 @@
</div>
<div class="changelog-content">
<ul>
<li>New checkpoints: minimind-3v (67M) / minimind-3v-moe (201M-A67M)</li>
<li>Projector: added LayerNorm, token merging switched to 2D pixel-shuffle</li>
<li>Vision Encoder switched to SiglipVisionModel (fixed 256×256)</li>
<li>New checkpoints: minimind-3v (65M) / minimind-3v-moe (200M-A65M)</li>
<li>Projector: added LayerNorm, removed reshape token merging (P32 natively outputs 64 tokens)</li>
<li>Vision Encoder switched to SiglipVisionModel (P32, fixed 256×256)</li>
<li>Training data moved to ALLaVA-4V (Pretrain 1.27M / SFT 2.9M, merged into single-stage SFT)</li>
<li>Freeze strategy: freeze_llm=1 unfreezes first + last layers; Pretrain/SFT defaults now 2/1; max_seq_len 360 → 450</li>
<li>Misc bugfixes and small tweaks</li>
@ -653,7 +653,7 @@
<ul>
<li>Added minimind-3v (67M) and minimind-3v-moe (201M-A67M) models</li>
<li>Unified 768+8 architecture, supporting both dense and moe modes</li>
<li>Switched Visual Encoder from CLIP to SigLIP2 (siglip2-base-p16-ve)</li>
<li>Switched Visual Encoder from CLIP to SigLIP2 (siglip2-base-p16-256-ve)</li>
<li>Replaced QFormer with MLP Projection + reshape compression</li>
<li>Dataset format updated to parquet, mixed data sources, updated tokenizer with image placeholder &lt;|image_pad|&gt;, new WebUI with dynamic model directory scanning and dropdown model switching</li>
<li>Model code refactored, LLM/VLM unified for Transformers format</li>