Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

Introducing StyleDrop, a model that allows a significantly higher level of stylized text-to-image synthesis by using a few style reference images that describe the style for text-to-image generation, bypassing the burden of text prompt engineering. More→

80,377 Aufrufe • vor 2 Jahren •via X (Twitter)

10 Kommentare

Profilbild von kache
kachevor 2 Jahren

model? code?

Profilbild von Alex Volkov (Thursd/AI) 🔜 AIENG summit NY
Alex Volkov (Thursd/AI) 🔜 AIENG summit NYvor 2 Jahren

Shoutout @natanielruizg 👏

Profilbild von Max (e/acc)
Max (e/acc)vor 2 Jahren

Could you please introduce Gemini (at least pro) to EU, and Gemini Ultra to the world?🙂

Profilbild von Digital Adam
Digital Adamvor 2 Jahren

@natanielruizg IPAdapter?

Profilbild von Nader Ale Ebrahim
Nader Ale Ebrahimvor 2 Jahren

Impressive work, @GoogleAI! This innovation promises to simplify the process and enhance the quality of text-to-image generation. Keep pushing the boundaries of AI research! 🌟 #AI #Research #Innovation

Profilbild von takeyourmeds
takeyourmedsvor 2 Jahren

watchumean introducing that's old stuff in stable diffusion like a year old

Profilbild von Rom_AI
Rom_AIvor 2 Jahren

Where is our access, Mr. Google?

Profilbild von Sumone .
Sumone .vor 2 Jahren

Just looking like a wow !!!

Profilbild von Mr.D
Mr.Dvor 2 Jahren

That sounds like an exciting advancement in text-to-image synthesis! StyleDrop seems to offer a more efficient approach by utilizing style reference images instead of relying solely on text prompts. This could potentially lead to more accurate and diverse image generation. I'm curious to learn more about how this model works and the results it can produce. @mira_hurley @TimeForPlanX

Profilbild von xiutai
xiutaivor 2 Jahren

@PublicAI_ #AI

Ähnliche Videos

We've officially released and open-sourced HunyuanImage 2.1, our latest text-to-image model. The new model delivers on our commitment to balancing performance and quality. With native 2K image generation, HunyuanImage 2.1 is an advanced open-source text-to-image model.🎨 ✨ New in 2.1: 🔹Advanced Semantics: Supports ultra-long and complex prompts of up to 1000 tokens, and precisely controls the generation of multiple subjects in a single image. 🔹Precise Chinese and English Text Rendering with seamless image–text integration: The model naturally integrates text into images, making it suitable for a wide range of applications such as product covers, illustrations, and poster design to meet the needs of various fields. 🔹Rich Styles and High Aesthetic: Capable of generating images in various styles—including photorealistic portraits, comics, and vinyl figures—it delivers outstanding visual appeal and artistic quality. 🔹High-Quality Generation: Efficiently produces ultra-high-definition (2K) images in the same time other models take to generate a 1K image. HunyuanImage 2.1 uses two text encoders: a multimodal large language model (MLLM) to improve the model's image and text alignment capabilities, and a multi-language character-aware encoder to improve text rendering capabilities. The model is a single- and double-stream diffusion transformer with 17B parameters. We've also open-sourced the weights of the the accelerated version with meanflow which reduces inference steps from 100 to just 8, and PromptEnhancer, the first industrial-grade rewriting model that enhances your prompts for more nuanced and expressive image generation. Now, creators turn complex ideas—like posters with slogans or multi-panel comics—into visuals faster than ever. We’re just getting started. Stay tuned for our native multimodal image generation model coming soon. 🌐Website: 🔗Github: 🤗Hugging Face: ✨Hugging Face Demo:

Tencent Hy

89,257 Aufrufe • vor 10 Monaten