Expand description
LLaVA Model V2 - Clean implementation using solid abstractions
This implements the LLaVA (Large Language and Vision Assistant) architecture including:
- LLaVA-1.5-7B, LLaVA-1.5-13B, LLaVA-1.6-7B, LLaVA-1.6-13B, LLaVA-1.6-34B
Architecture components:
- Vision Tower: CLIP-style vision encoder with patch embeddings and bidirectional attention
- Multimodal Projector: Projects vision features to language model dimension (Linear or MLP)
- Language Model: LLaMA-style decoder with RoPE, GQA, and SwiGLU MLP
Structsยง
- LLaVA
Config - LLaVA
Language Attention - LLaMA-style Attention with RoPE and GQA
- LLaVA
Language Layer - LLaMA-style Transformer Layer
- LLaVA
LanguageMLP - LLaMA-style MLP with SwiGLU
- LLaVA
Language Model - Complete Language Model
- LLaVA
Model V2 - Complete LLaVA Model
- LLaVA
Multi Modal Projector - Projects vision features to language model dimension
- LLaVA
Vision Attention - CLIP Vision Attention (bidirectional, no causal mask)
- LLaVA
Vision Embeddings - CLIP-style Vision Embeddings
- LLaVA
Vision Encoder - CLIP Vision Encoder
- LLaVA
Vision Layer - CLIP Vision Encoder Layer
- LLaVA
VisionMLP - CLIP Vision MLP (GELU activation)
- LLaVA
Vision Tower - Complete Vision Tower (CLIP ViT)