denoising-diffusion-pytorch
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denoising-diffusion-pytorch | guided-diffusion | |
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11 | 14 | |
6,994 | 5,439 | |
- | 2.9% | |
8.6 | 0.0 | |
14 days ago | about 1 year ago | |
Python | Python | |
MIT License | MIT License |
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denoising-diffusion-pytorch
- Commits · lucidrains/denoising-diffusion-pytorch
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Help using torchaudio and spectrograms for diffusion
I’m trying to train a diffusion model using this code (https://github.com/lucidrains/denoising-diffusion-pytorch). My idea is to take a short audio segment, transform it into a spectrogram and train the model on these images then have it generate spectrograms then go back to audio. However the model requires square images. I cannot for the life of me figure out how to make a square spectrogram. Also is a regular spectrogram or a mel spectrogram better for this application?
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Implementation of Google's MusicLM in PyTorch
Generally it's without weights, but MusicLM is also a WIP more mature implementations have descriptions on how to train them and follow ups on small scale/crowd-sourced experiments & research[1].
[1]: https://github.com/lucidrains/denoising-diffusion-pytorch
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[D] Time Embedding in Diffusion Model
[1] https://colab.research.google.com/drive/1sjy9odlSSy0RBVgMTgP7s99NXsqglsUL?usp=sharing#scrollTo=KOYPSxPf_LL7 [2] https://github.com/lucidrains/denoising-diffusion-pytorch/blob/main/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py
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[D] Can a Diffusion Model be trained with an NVIDIA TITAN X?
Sure. I am using: https://github.com/lucidrains/denoising-diffusion-pytorch
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[D] Resources to learn and fully understand Diffusion Model Codes
Lucidrains GitHub is always my go to repo for understandable paper implementations https://github.com/lucidrains/denoising-diffusion-pytorch
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Diffusion model generated exactly the same image as the training image
Thanks for the reply. Is there any suggestion if I wanted to train a model to generate half cat and half butterfly images what I should do? I git cloned the code from https://github.com/lucidrains/denoising-diffusion-pytorch and trained from scratch.
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[D] Best diffusion model archetype to train?
DDIM/DDPM are the same model to train, they only differ at inference time. To start I would recommend building from lucidrains' MIT licenced version (https://github.com/lucidrains/denoising-diffusion-pytorch). Just play around with the models until you gain an intuition.
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We just release a complete open-source solution for accelerating Stable Diffusion pretraining and fine-tuning!
Our codebase for the diffusion models builds heavily on OpenAI's ADM codebase , lucidrains, Stable Diffusion, Lightning and Hugging Face. Thanks for open-sourcing!
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[D] Introduction to Diffusion Models
Once you understand these papers you can begin to understand Palette, and from there I would start with an open-source diffusion implementation like this one and then modify it to suit your needs!
guided-diffusion
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Why is there speculation that midjourney is based on stable diffusion if MJ is released earlier than SD?
People who made these colabs better and better also the same people who are at Midjourney now. But the "mother" of it all, was Katherine Crowson. She made a fine tuned model that uses a 512x512 unconditional ImageNet diffusion model fine-tuned from OpenAI's 512x512 class-conditional ImageNet diffusion model (https://github.com/openai/guided-diffusion) together with CLIP (https://github.com/openai/CLIP) to connect text prompts with images. It uses a smaller secondary diffusion model trained by Katherine Crowson to remove noise from intermediate timesteps to prepare them for CLIP.
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Any Tips on OpenAI's Guided Diffusion?
I am trying to use OpenAI's Guided Diffusion Github to train my own diffusion model. I thought to ask here to see if anyone had any experience with it as I've been having trouble training my own models on it. If anyone has any resources to point me towards it would be greatly appreciated!
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We just release a complete open-source solution for accelerating Stable Diffusion pretraining and fine-tuning!
Our codebase for the diffusion models builds heavily on OpenAI's ADM codebase , lucidrains, Stable Diffusion, Lightning and Hugging Face. Thanks for open-sourcing!
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guided diffusion super resolution network training is diverging
I am working with guided diffusion. I would like to reproduce the results of the repository for the 64->256 super resolution network. https://github.com/openai/guided-diffusion
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New custom inpainting model
this code is (mostly) just the original openai guided diffusion code: https://github.com/openai/guided-diffusion
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Tips for Training Diffusion Model (DD) With Images and Resource Links
Starting resource, as it is all done through this code (information on how to do it on Colab is out there) https://github.com/openai/guided-diffusion
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What was Disco trained with?
Original notebook by Katherine Crowson (https://github.com/crowsonkb, https://twitter.com/RiversHaveWings). It uses either OpenAI's 256x256 unconditional ImageNet or Katherine Crowson's fine-tuned 512x512 diffusion model (https://github.com/openai/guided-diffusion), together with CLIP (https://github.com/openai/CLIP) to connect text prompts with images.
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[D] Diffusion Models Beat GANs on Image Synthesis Explained: 5-minute paper summary (by Casual GAN Papers)
Code for https://arxiv.org/abs/2105.05233 found: https://github.com/openai/guided-diffusion
- "Everything the AI can create" using diffusion model
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Since this sub has a fair portion of AI-generated images, have you guys seen OpenAI's guided diffusion models yet?
Paper, repo, Colab. It's really good.
What are some alternatives?
ALAE - [CVPR2020] Adversarial Latent Autoencoders
disco-diffusion
autoregressive - :kiwi_fruit: Autoregressive Models in PyTorch.
score_sde - Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
stylegan2-pytorch - Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Awesome-Diffusion-Models - A collection of resources and papers on Diffusion Models
pytorch-lightning - Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
RAVE - Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder
ColossalAI - Making large AI models cheaper, faster and more accessible
glid-3-xl-stable - stable diffusion training