SEED

Why we included this project

SEED-LLaMA is a research-grade multimodal model that handles image understanding and image generation inside one large language model, which makes it a useful reference if you are studying how vision and language can be fused rather than bolted together. The repo includes the full training pipeline: the SEED tokenizer that converts visual signals into discrete tokens, plus pretraining and instruction-tuning code for the 8B and 14B variants, so researchers can reproduce the method or adapt it to their own work. The released checkpoints also run on a single 16GB or 24GB GPU thanks to 8-bit quantization and dynamic loading, and an online Gradio demo lets you try the assistant-style multimodal chat before setting anything up locally. Since this is the official implementation behind the ICLR 2024 papers, treat it as a reference codebase and research starting point rather than a turnkey product.