parti-pytorch
muse-maskgit-pytorch
| parti-pytorch | muse-maskgit-pytorch | |
|---|---|---|
| 2 | 5 | |
| 508 | 818 | |
| - | - | |
| 5.5 | 5.6 | |
| 6 months ago | 3 months ago | |
| Python | Python | |
| MIT License | MIT License |
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parti-pytorch
- Google Parti open source implementation
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Pathways Autoregressive Text-to-Image Model (Parti)
Give it a few days and lucidrains will have the code up[0].
But in honesty, it is probably how people react. We saw this with Pulse, GPT, and many others. The authors are clear about the limitations but people talk it up too much and others shit on it. There's also a reproducibility crisis in ML (many famous networks, like Swin[1][2][3], can't be reproduced (even worse when reviewers concentrate on benchmarks)). It isn't like many can train a model like this anyways. It gives them benefit of the doubt and maintains good publicity rather than controversial.
Of course, this is extremely bad from an academic perspective and personally I believe you should have your paper revoked if it isn't reproducible. You'd be surprised how many don't track the random seed or measure variance. We have GitHub. You should be able to write training options that get approximately the same results as the paper. Otherwise I don't trust your results.
[0] https://github.com/lucidrains/parti-pytorch
[1] https://github.com/microsoft/Swin-Transformer/issues/183
[2] https://github.com/microsoft/Swin-Transformer/issues/180
[3] https://github.com/microsoft/Swin-Transformer/issues/148
muse-maskgit-pytorch
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Google's StyleDrop can transfer style from a single image
If google doesnt, someone like lucidrains probably would implement it, just like he did for imagen and muse.
- GitHub - lucidrains/muse-maskgit-pytorch: Implementation of Muse: Text-to-Image Generation via Masked Generative Transformers, in Pytorch
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Muse: Text-to-Image Generation via Masked Generative Transformers
here is an available implementation:
https://github.com/lucidrains/muse-maskgit-pytorch
- Google just announced an Even better diffusion process.
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Muse: Text-To-Image Generation via Masked Generative Transformers (Google Research)
I went to check and yes, lucidrains already has a repo to implement this.
What are some alternatives?
Swin-Transformer - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
imagen-pytorch - Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch
DALLE-pytorch - Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
musiclm-pytorch - Implementation of MusicLM, Google's new SOTA model for music generation using attention networks, in Pytorch
deep-daze - Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network). Technique was originally created by https://twitter.com/advadnoun
toolformer-pytorch - Implementation of Toolformer, Language Models That Can Use Tools, by MetaAI
soundstorm-pytorch - Implementation of SoundStorm, Efficient Parallel Audio Generation from Google Deepmind, in Pytorch
iTransformer - Unofficial implementation of iTransformer - SOTA Time Series Forecasting using Attention networks, out of Tsinghua / Ant group