GlueGen: Plug and Play Multi-modal Encoders for X-to-image Generation

Other authors include: Can Qin, Stefano Ermon, Yun Fu GlueGen was accepted by ICCV. In the rapidly advancing field of text-to-image synthesis, the remarkable progress in generating lifelike images from textual prompts has been evident. However, a significant challenge remains: how can we seamlessly integrate powerful pre-trained text encoders into

29 Sep 2023 •

Open Source and the Future of Enterprise AI

Introduction Open source has become one of the hottest topics in AI, and the fanfare is well-deserved. The open source community is keeping a nimble pace with the state of the art, delivering ever-growing and ever-more-capable models that often compete impressively with their commercial counterparts. It’s an exciting thing

25 Sep 2023 •

CodeGen2.5: Small, but mighty

Equal contribution between Erik Nijkamp and Hiroaki Hayashi. Paper Code Tweet Abstract The family of Salesforce CodeGen models is growing with CodeGen2.5 – a small, but mighty model! While there has been a recent trend of large language models (LLM) of increasing size, we show that a small model can

06 Jul 2023 • #CodeGen