Karlo 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.

Pricing

Pricing Starts At:
Free
Pricing Information:
Open source
Free Version:
Yes

Integrations

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Company Details

Company:
Kakao Brain
Year Founded:
2017
Headquarters:
South Korea
Website:
github.com/kakaobrain/karlo

Media

Karlo Screenshot 1
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Product Details

Platforms
Web-Based
On-Premises
Types of Training
Training Docs

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