diff --git a/images/VLM-structure-moe.jpg b/images/VLM-structure-moe.jpg new file mode 100644 index 0000000..a42f967 Binary files /dev/null and b/images/VLM-structure-moe.jpg differ diff --git a/images/VLM-structure-moe.png b/images/VLM-structure-moe.png deleted file mode 100644 index 8c5aec1..0000000 Binary files a/images/VLM-structure-moe.png and /dev/null differ diff --git a/images/VLM-structure.jpg b/images/VLM-structure.jpg new file mode 100644 index 0000000..33a97e6 Binary files /dev/null and b/images/VLM-structure.jpg differ diff --git a/images/VLM-structure.png b/images/VLM-structure.png deleted file mode 100755 index 944c559..0000000 Binary files a/images/VLM-structure.png and /dev/null differ diff --git a/images/minimind-3v.gif b/images/minimind-3v.gif new file mode 100644 index 0000000..c91a875 Binary files /dev/null and b/images/minimind-3v.gif differ diff --git a/images/minimind2-v.gif b/images/minimind2-v.gif deleted file mode 100644 index c115799..0000000 Binary files a/images/minimind2-v.gif and /dev/null differ diff --git a/index.html b/index.html index 4290d58..43cf4de 100644 --- a/index.html +++ b/index.html @@ -528,7 +528,7 @@

- Train a 26M Vision-Language Model from zero.
+ Train a 67M Vision-Language Model from zero.
1 hour. ¥1.3. One 3090.
See the World.

@@ -537,7 +537,7 @@
-

26M

+

67M

Parameters

@@ -549,7 +549,7 @@

Cost

-

1/7000

+

1/2600

vs GPT-3

@@ -563,7 +563,7 @@

📦 Complete VLM Stack

-

Vision encoder → LLM → Projector → Pretrain → SFT

+

SigLIP2 encoder → LLM → Projector → Pretrain → SFT

💰 Ultra-Affordable

@@ -596,16 +596,28 @@ + + minimind-3v-moe + 202M-A67M + 1.0 GB + 2026.04.01 + + + minimind-3v + 67M + 0.5 GB + 2026.04.01 + MiniMind2-V 104M - 0.6 GB + 1.1 GB 2025.02.20 MiniMind2-Small-V 26M - 1.1 GB + 0.6 GB 2025.02.20 @@ -617,15 +629,33 @@
- 🎉 2025-10-24 (Latest) + 🎉 2026-04-01 (Latest) −
    -
  • Bug fix: Model weight mismatch issue resolved
  • -
  • Adapted to minimind-1024 updates
  • -
  • Code refactoring: Training and evaluation script standardization
  • -
  • Added complete checkpoint resumption support
  • +
  • Added minimind-3v (67M) and minimind-3v-moe (201M-A67M) models
  • +
  • Unified 768+8 architecture, supporting both dense and moe modes
  • +
  • Switched Visual Encoder from CLIP to SigLIP2 (siglip2-base-p16-ve)
  • +
  • Replaced QFormer with MLP Projection + reshape compression
  • +
  • Dataset format updated to parquet, mixed data sources, updated tokenizer with image placeholder <|image_pad|>, new WebUI with dynamic model directory scanning and dropdown model switching
  • +
  • Model code refactored, LLM/VLM unified for Transformers format
  • +
  • Training scripts support DDP multi-GPU, bfloat16 mixed precision, torch.compile acceleration
  • +
+
+
+ +
+
+ 🛠️ 2025-10-24 + + +
+
+
    +
  • Bug fix: mismatched model weights
  • +
  • Adapted to the latest minimind updates
  • +
  • Refactored training and evaluation scripts
  • +
  • Added complete checkpoint resume support
@@ -678,9 +708,9 @@
🎮 Inside MiniMind-V
- MiniMind-V Demo - VLM Structure - VLM Structure MOE + MiniMind-V Demo + VLM Structure + VLM Structure MOE
@@ -706,7 +736,7 @@ GitHub Repo - + 🤗 HuggingFace