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What is Stable Diffusion?

In recent times, we have been genuinely appreciative of the substantial feedback received, and we are committed to executing a launch that prioritizes responsibility and security, taking into account the valuable insights acquired from beta testing and community input for our developers to integrate. By working hand in hand with the dedicated legal, ethics, and technology teams at HuggingFace, alongside the talented engineers at CoreWeave, we have successfully developed an integrated AI Safety Classifier within our software package. This classifier is specifically engineered to understand diverse concepts and factors during content generation, allowing it to screen outputs that may not meet user expectations. Users have the flexibility to modify the parameters of this feature, and we wholeheartedly welcome suggestions from the community for further improvements. Although image generation models exhibit remarkable potential, there is still an ongoing necessity for progress in accurately aligning results with our desired objectives. Our ultimate aim remains to enhance these tools continually, ensuring they effectively adapt to the changing requirements of users and foster a collaborative environment for innovation.

What is Karlo?

Karlo is an advanced model crafted to generate images from written descriptions, building upon the remarkable unCLIP architecture created by OpenAI by refining the standard super-resolution model to effectively capture intricate details at a notable resolution of 256px while minimizing noise through a limited series of denoising iterations. The development of Karlo involved an extensive training process that commenced from scratch, utilizing a large dataset of 115 million image-text pairs, which encompassed sources like COYO-100M, CC3M, and CC12M. In constructing the Prior and Decoder components, we implemented the sophisticated ViT-L/14 text encoder from OpenAI's CLIP library. To enhance the model’s performance, we made a significant modification to the original unCLIP framework; instead of employing a trainable transformer within the decoder, we integrated the text encoder from ViT-L/14, significantly boosting the model's potential. This strategic modification not only simplified the architectural design but also played a crucial role in enhancing both the quality and fidelity of the generated images, thus marking a significant advancement in the field. Overall, Karlo's innovative approach represents a meaningful step forward in the integration of text and visual content.

Media

Media

Integrations Supported

AI Picasso
Aitubo
Akuma
Amazon Bedrock
B^ DISCOVER
Dreamlook
FY! Studio
Headshots by AI
IMLAZY AI
LastMile AI
Lewis
LlamaIndex
Mobile Diffusion
Model Playground
Overseer AI
PXZ AI
PromptPerfect
Pruna AI
Unremot
VisionFX

Integrations Supported

AI Picasso
Aitubo
Akuma
Amazon Bedrock
B^ DISCOVER
Dreamlook
FY! Studio
Headshots by AI
IMLAZY AI
LastMile AI
Lewis
LlamaIndex
Mobile Diffusion
Model Playground
Overseer AI
PXZ AI
PromptPerfect
Pruna AI
Unremot
VisionFX

API Availability

Has API

API Availability

Has API

Pricing Information

$0.2 per image
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Stability AI

Company Location

United Kingdom

Company Website

stability.ai/blog/stable-diffusion-public-release

Company Facts

Organization Name

Kakao Brain

Date Founded

2017

Company Location

South Korea

Company Website

github.com/kakaobrain/karlo

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