ethan cohen

Hi, here is my script (I followed the instruction in the readme.) When using image_size=128 it works fine, otherwise it does not. import torch from denoising_diffusion_pytorch import Unet, GaussianDiffusion, Trainer...

Sorry bout that, I was using an older version, thanks. I now can generate higher size but 300 doesnt seems to work but that okay size 256 is fine ...

Actually I want to get something as in High-Resolution Image Synthesis with Latent Diffusion Models since I want to be able to encode from any source of data. I guess...

oh thats awesome ! any idea how I can do that ? If I have a condition x and I create an encoder T(x) and I want to generate images...

yes i saw this repo ( which is awesome btw ) but only thing is that I cannot do any clip training as I dont have text conditionning but features...

Yep if there is a training script for text2image that would be great !

Hey, Has it been released yet ? By looking at #356 it seems like the code is for finetunning. Is it planned to have a training pipeline from scratch (or...

Perfect, thank you very much for your reactivity :) When you say load random models is it like with the transformers library where you define the config for the model...

Also yo you have any idea on the different performance of stable diffusion based on way the conditiioning is incorporated (clip based vs scratch based vs pretrained text based for...

Anyone has an idea about this ? @lucidrains