Implementation of Classifier Free Guidance in Pytorch, with emphasis on text conditioning, and flexibility to include multiple text embedding models
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Updated
Oct 6, 2024 - Python
Implementation of Classifier Free Guidance in Pytorch, with emphasis on text conditioning, and flexibility to include multiple text embedding models
Creating a diffusion model from scratch in PyTorch to learn exactly how they work.
Remaining Useful Life estimation and sensor data generation by VAE and diffusion model on C-MAPSS dataset.
ReNeg: Learning Negative Embedding with Reward Guidance
The implementation for "3D Scene Diffusion Guidance using Scene Graphs" paper. A Diffusion Model for Conditional 3D Scene Generation with Classifier-Free Guidance on Scene Graphs
Exploring classifier-free guidance in a DDPM language model for text generation towards emotion targets.
extension for Forge webui; methods to modify the CFG during diffusion; can bypass uncond calculations for free performance gain
A Simplified notebook for Smoothed Energy Guidance utilised for Stable Diffusion 2.1 base
PyTorch implementation of 'CFG' (Ho et al., 2022).
DDPM (Denoising Diffusion Probabilistic Models) and DDIM (Denoising Diffusion Implicit Models) for conditional image generation
DogFusion: Dog Image Generation.
A PyTorch implementation of DDPM
In this project, you will find an implementation of a diffusion model, trained on images of handwritten numbers from the MNIST dataset.
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