Benin Multimodal AI Hackathon

On-site registration and Welcoming participants

On-site Opening Ceremony

On-site Networking and Team Formation

Official Hackathon Start

Online Hackathon Kick-off Stream

Lablab Workshop - Ampas Theodoros & Donald Nwokoro - Local language to image

Google Workshop - Mehrnoosh Vahdat -GenAI with Google Cloud

End of Submissions

ANGO TECH

Anuprabha0705

AG1007


Text-to-image generation refers to the process of creating visual images from text descriptions or captions. This technology leverages machine learning models, particularly deep learning architectures like generative adversarial networks (GANs) and diffusion models, to convert textual information into pixel-based representations.
The process typically involves training a neural network on a large dataset of images and their corresponding captions or descriptions. During training, the model learns to associate specific patterns in the text with visual features in the images. Once trained, the model can generate new images based on previously unseen text prompts.
Some popular text-to-image models include Stable  These models can generate highly realistic and diverse images based on user-provided text descriptions, enabling a wide range of creative applications in fields like art, design, advertising, and content creation.


The Text-to-Image Generation project utilizing Hugging Face showcases the fusion of advanced natural language processing and computer vision technologies. 

ANGO AI

"ANGO TECH team on Benin Multimodal AI Hackathon Hackathon"

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