lightning
denoising-diffusion-pytorch
lightning | denoising-diffusion-pytorch | |
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50 | 11 | |
2,762 | 7,032 | |
0.4% | - | |
9.9 | 8.5 | |
2 days ago | 19 days ago | |
C | Python | |
GNU General Public License v3.0 or later | MIT License |
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lightning
- Opening channel from external wallet in Core Lightning
- Obtain gossip messages without node
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Craig falsely insists that the Lightning Network is infringing on nChain's patents for a CBDC
Wait until they realize Craig Wright's Cryptographic Proof was there all along.
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Lightning node on a pruned bitcoind
https://github.com/ElementsProject/lightning/issues/5310.
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Serious Question about Bitcoin
c-lightning, developed by [Blockstream]
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Run a node
LND - https://github.com/lightningnetwork/lnd CLN - https://github.com/ElementsProject/lightning
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š MiniBolt resources š List of the MiniBolt core/bonus guides + latest versions
Core Lightning (CLN) v.22.11 (Released 30th November 2022) - https://github.com/ElementsProject/lightning/releases
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Can't open channels on my Linux VM Core Lightning implementation
I opened an issue on the Core Lightning repo. It has a complete list of the logs that were happening that caused the peer to drain and disconnect https://github.com/ElementsProject/lightning/issues/5816
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How to use the lightning network without apps.
A country can't stop you from running lnd or Core Lightning, so I'm not sure what you're talking about?
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ā” RaspiBolt Improvement Proposals (RBIPs) & Bounties š°
Power cuts can lead to node corruption (e.g. here)
denoising-diffusion-pytorch
- Commits Ā· lucidrains/denoising-diffusion-pytorch
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Help using torchaudio and spectrograms for diffusion
Iām 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!
What are some alternatives?
lnd - Lightning Network Daemon ā”ļø
ALAE - [CVPR2020] Adversarial Latent Autoencoders
Eclair - A scala implementation of the Lightning Network.
autoregressive - :kiwi_fruit: Autoregressive Models in PyTorch.
umbrel - A beautiful home server OS for self-hosting with an app store. Buy a pre-built Umbrel Home with umbrelOS, or install on a Raspberry Pi 4, Pi 5, any Ubuntu/Debian system, or a VPS.
stylegan2-pytorch - Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
zeus - A mobile Bitcoin wallet fit for the gods. ā”ļø Est. 563345
RAVE - Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder
RTL - Ride The Lightning - A full function web browser app for LND, C-Lightning and Eclair
Awesome-Diffusion-Models - A collection of resources and papers on Diffusion Models
raspiblitz - Get your own Bitcoin & Lightning Node running - on a RaspberryPi with a nice LCD
pytorch-lightning - Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.