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Description
DALL·E 2 is capable of generating unique and lifelike images and artwork from textual prompts. It adeptly melds various concepts, attributes, and artistic styles into cohesive visuals. The tool can also extend images beyond their initial boundaries, leading to the creation of expansive new artworks. Moreover, DALL·E 2 can execute realistic modifications to existing images based on natural language descriptions. It is able to seamlessly add or remove elements while considering factors like shadows, reflections, and textures. Through its training, DALL·E 2 has developed an understanding of how images correlate with their textual descriptions. Utilizing a technique known as “diffusion,” it begins with a chaotic arrangement of dots and progressively refines them into a coherent image as it identifies distinct features. Our content policy strictly prohibits the generation of images that include violent, adult, or politically sensitive themes, among other restricted categories. Consequently, if our filters detect any prompts or uploads that may breach these guidelines, we will refrain from producing the corresponding images. Additionally, we employ a combination of automated systems and human oversight to prevent any potential misuse of the platform. This comprehensive monitoring ensures a safe and responsible use of DALL·E 2 across various applications.
Description
Karlo serves as an innovative model designed to create images from textual descriptions. It enhances the impressive unCLIP architecture developed by OpenAI by improving the conventional super-resolution model, enabling it to capture complex details at an impressive resolution of 256px, while effectively reducing noise through a limited number of denoising iterations.
In developing Karlo, we undertook a comprehensive training regimen that began from the ground up, leveraging a substantial dataset of 115 million image-text pairs, which included COYO-100M, CC3M, and CC12M. For the Prior and Decoder sections, we utilized the advanced ViT-L/14 text encoder sourced from OpenAI's CLIP library. To boost performance, we implemented a notable alteration to the original unCLIP design; rather than using a trainable transformer in the decoder, we opted to incorporate the text encoder from ViT-L/14, thereby enhancing the model's capability. This strategic choice not only streamlined the architecture but also contributed to improved image quality and fidelity.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Amazon SageMaker Model Training
Yes
Bing Image Creator
Yes
Coursiv
Yes
DeskFerry
Yes
Freeflo
Yes
GLM-Image
Yes
GMTech
Yes
Hippo AI
Yes
LaPrompt
Yes
LibreChat
Yes
Integrations
Amazon SageMaker Model Training
No
Bing Image Creator
No
Coursiv
No
DeskFerry
No
Freeflo
No
GLM-Image
No
GMTech
No
Hippo AI
No
LaPrompt
No
LibreChat
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
Free
Open source
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
OpenAI
Founded
2015
Country
United States
Website
openai.com/dall-e-2/
Vendor Details
Company Name
Kakao Brain
Founded
2017
Country
South Korea
Website
github.com/kakaobrain/karlo
