福模

免费开源AI模型下载_本地AI工具资源平台

生成模型Generative Models

Imagen AI图像生成模型 - 高保真文本到图像合成

Imagen AI Image Generation Model - High-Fidelity Text-to-Image Synthesis

Imagen AI图像生成模型,基于扩散模型的高保真文本到图像合成系统。能够生成高质量、高分辨率的图像,匹配文本描述的细节。

Imagen AI image generation model, a high-fidelity text-to-image synthesis system based on diffusion models. Capable of generating high-quality, high-resolution images matching the details of text descriptions.

Imagen图像生成文本到图像高保真ImagenImage GenerationText-to-ImageHigh-Fidelity

文件大小

16.5 GB

Upload Size

16.5 GB

上传日期

2025-02-09

Upload Date

2025-02-09

下载次数

15,700

Downloads

15,700

评分

4.8/5.0

Rating

4.8/5.0

下载资源 Download Resources

下载资源表示您同意我们的使用条款和隐私政策

By downloading this resource, you agree to our Terms of Service and Privacy Policy

相关资源推荐

StyleGAN3人脸生成模型 - 高保真头像与人物图像创建StyleGAN3 Face Generation Model - High-Fidelity Avatar and Character Image Creation

StyleGAN3人脸生成模型,用于高保真头像与人物图像创建。可生成逼真的人物肖像,支持年龄、表情、性别等属性精细调节,广泛应用于虚拟角色和游戏角色设计。

StyleGAN3 face generation model, used for high-fidelity avatar and character image creation. Generates realistic human portraits with fine control over attributes like age, expression, gender, widely used in virtual characters and game character design.

StyleGAN3人脸生成头像创建StyleGAN3Face GenerationAvatar Creation
18.9 GB2025-01-03
ProGAN渐进式生成AI模型 - 高分辨率图像合成ProGAN Progressive Generation AI Model - High-Resolution Image Synthesis

ProGAN渐进式生成AI模型,能够逐步生成高分辨率图像。从低分辨率开始逐渐增加细节,生成逼真的图像,广泛应用于艺术和设计领域。

ProGAN progressive generation AI model, capable of generating high-resolution images progressively. Starting from low resolution and gradually increasing detail, generating realistic images, widely used in art and design fields.

ProGAN渐进式生成高分辨率ProGANProgressive GenerationHigh Resolution
9.1 GB2025-02-01
ControlNet条件控制模型 - 精确控制AI图像生成ControlNet Conditional Control Model - Precise Control of AI Image Generation

ControlNet条件控制模型,实现精确控制AI图像生成的模型。通过额外的条件输入,如边缘图、姿态图等,可以精确控制生成图像的结构和布局,提升生成结果的可控性。

ControlNet conditional control model, a model achieving precise control of AI image generation. Through additional conditional inputs, such as edge maps, pose diagrams, etc., it enables precise control of the structure and layout of generated images, enhancing the controllability of generation results.

ControlNet条件控制图像生成ControlNetConditional ControlImage Generation
15.2 GB2024-12-22