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
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
PyTorch implementation of 'CFG' (Ho et al., 2022).
DogFusion: Dog Image Generation.
A PyTorch implementation of DDPM
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