Published inTowards Data Science·PinnedMember-onlyHow to Fine-tune Stable Diffusion using DreamboothPersonalized generated images with custom styles or objects — Previously, I have covered an article on fine-tuning Stable Diffusion using textual inversion. This tutorial focuses on how to fine-tune Stable Diffusion using another method called Dreambooth. Unlike textual inversion method which train just the embedding without modification to the base model, Dreambooth fine-tune the whole text-to-image model such that…Python10 min readPython10 min read
Published inTowards Data Science·PinnedMember-onlyHow to Fine-tune Stable Diffusion using Textual InversionPersonalized generated images with custom styles or objects — On 22 Aug 2022, Stability.AI announced the public release of Stable Diffusion, a powerful latent text-to-image diffusion model. The model is capable of generating different variants of images given any text or image as input. Please note that the … model is being released under a Creative ML OpenRAIL-M license…Artificial Intelligence7 min readArtificial Intelligence7 min read
May 26Member-onlyIntroduction to Kandinsky 2.1A multilingual text2image latent diffusion model Kandinsky 2.1 is a new multilingual text2image latent diffusion model that inherits best practices from its predecessor DALL-E 2 and Latent Diffusion. Besides that, it also introduces a few new ideas for text-guided image manipulation and image fusing (interpolation). Most of the open-sourced multilingual…Text To Image Generation5 min readText To Image Generation5 min read
May 8Member-onlyIntroduction to WeTextProcessing: Chinese Text NormalizationNormalize chinese text for downstream tasks By reading this piece, you will learn to perform chinese text normalization and inverse text normalization. Text normalization is one of the most important preprocessing steps in natural language processing (NLP). Most of the time, raw text should not be used directly for any…Python3 min readPython3 min read
May 5Member-onlyIntroduction to Shap-E: Text-to-3DGenerate 3D objects conditioned on text or images By reading this article, you will learn to use Shap-E for 3D objects generation. As of 5 May 2023, OpenAI officially released Shap-E, which is a system to generate 3D objects conditioned on text or images Similar to its predecessor Point-E, Shap-E…Python5 min readPython5 min read
Apr 6Member-onlyIntroduction to Token Merging for Stable DiffusionSpeeds up image generation by merging redundant tokens The topic for today is on Token Merging (ToMe) to speed up image generating by merging redundant tokens. The token merging concept was first introduced by the team behind Facebook research. Token Merging (ToMe) … allows you to take an existing Vision…Python4 min readPython4 min read
Mar 30Member-onlyIntroduction to VideoFusionDecomposed Diffusion Models for High-Quality Video Generation By reading this article, you will learn to perform text-to-video generation using TextToVideoSDPipeline, a new pipeline based on the VideoFusion paper. It is available in the development version of the diffusers package (0.15.0.dev0). VideoFusion is a new research initiative by the Damo Vilab…Python5 min readPython5 min read
Mar 21Member-onlyIntroduction to Lifespan Events in FastAPINew implementation for startup and shutdown logic By reading this piece, you will learn to implement lifespan events in your FastAPI for startup and shutdown logic. From version 0.93.0 onward, the fastapi module officially supports the lifespan event, which replaces the startup and shutdown events. startup and shutdown events will…Python3 min readPython3 min read
Mar 8Member-onlyIntroduction to ControlNet for Stable DiffusionBetter control for text-to-image generation This tutorial covers a step-by-step guide on text-to-image generation with ControlNet conditioning using the HuggingFace’s diffusers package. ControlNet is a neural network structure to control diffusion models by adding extra conditions. It provides a way to augment Stable Diffusion with conditional inputs such as scribbles…Stable Diffusion7 min readStable Diffusion7 min read
Mar 6Member-onlyHow to Speed Up Data Loading for Machine Learning TrainingBased on the HuggingFace’s datasets package The topic for today is about how to speed up the data loading process using the HuggingFace’s datasets package. For your information, the datasets module is part of the HuggingFace’s data loader ecosystem. It serves as an easy-to-use and efficient data manipulation tools. …Datasets For Ml4 min readDatasets For Ml4 min read