text-to-text-transfer-tra
imagen-pytorch
text-to-text-transfer-tra | imagen-pytorch | |
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2 | 47 | |
- | 7,807 | |
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- | 6.6 | |
- | 18 days ago | |
Python | ||
- | MIT License |
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text-to-text-transfer-tra
- AlphaCode by DeepMind
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New text-to-image network from Google beats DALL-E
T5 was open-sourced on release (up to 11B params): https://github.com/google-research/text-to-text-transfer-tra...
It is also available via Hugging Face transformers.
Unclear if 11B is the T5-XXL mentioned in the paper, however.
imagen-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.
- Create a Stable diffusion neural network from scratch.
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Google just announced an Even better diffusion process.
lucidrains/imagen-pytorch: Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch (github.com)
- Karlo, the first large scale open source DALL-E 2 replication is here
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training imagen
Hi Can someone guide me a little, as to how i can use LAION dataset to train my imagen model? like how i can download the data, and in which format it should be fed to https://github.com/lucidrains/imagen-pytorch code?
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If everyone in this sub make a donation of $10 then we can train truly open stable diffusion.
If we were to put money into training something, I'd hope we use a better model, like Imagen.
- AI Content Generation, Part 1: Machine Learning Basics
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DALL-E 2 is switching to a credits system (50 generations for free at first, 15 free per month)
I've been messing around with this open-source implementation. You can get a pretty good idea of the model size by just copying the parameters from the paper.
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Protests erupt outside of DALL-E offices after pricing implementation, press photograph
I'm waiting on this implementation/training of imagen: https://github.com/lucidrains/imagen-pytorch
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Show HN: Food Does Not Exist
I'm honestly surprised that they trained a StyleGAN. Recently, the Imagen architecture has been show to be both easier in structure, easier to train, and even faster to produce good results. Combined with the "Elucidating" paper by NVIDIA's Tero Karras you can train a 256px Imagen to tolerable quality within an hour on a RTX 3090.
Here's a PyTorch implementation by the LAION people:
https://github.com/lucidrains/imagen-pytorch
And here's 2 images I sampled after training it for some hours, like 2 hours base model + 4 hours upscaler:
https://imgur.com/a/46EZsJo
What are some alternatives?
tortoise-tts - A multi-voice TTS system trained with an emphasis on quality
dalle-mini - DALLĀ·E Mini - Generate images from a text prompt
text-to-text-transfer-transformer - Code for the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"
DALLE2-pytorch - Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
majesty-diffusion - Majesty Diffusion by @Dango233(@Dango233max) and @apolinario (@multimodalart)
DALLE-pytorch - Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
DeepCreamPy - deeppomf's DeepCreamPy + some updates
latent-diffusion - High-Resolution Image Synthesis with Latent Diffusion Models
hent-AI - Automation of censor bar detection
CogVideo - Text-to-video generation. The repo for ICLR2023 paper "CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers"