glid-3-xl
glide-text2im
glid-3-xl | glide-text2im | |
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7 | 32 | |
255 | 3,470 | |
- | 0.6% | |
0.0 | 0.0 | |
almost 2 years ago | 2 months ago | |
Python | Python | |
MIT License | MIT License |
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glid-3-xl
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Run Your Own DALL·E Mini (Craiyon) Server on EC2
If you’re anything like us, though, you’ll feel compelled to poke around the code and run the model yourself. We’ll do that in this article using Meadowrun, an open-source library that makes it easy to run Python code in the cloud. For ML models in particular, we just added a feature for requesting GPU machines in a recent release. We’ll also feed the images generated by DALL·E Mini into additional image processing models (GLID-3-xl and SwinIR) to improve the quality of our generated images. Along the way we’ll deal with the speedbumps that come up when running open-source ML models on EC2.
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[D] Has anyone trained the latent diffusion models by OpenAI(CompVis)? Need some help
Personally, I've found GLID3 and GLID3-XL to be nice and straightforward. Worked right out of the box.
- [D] Any relatively new text2image models with fine tuning?
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Trying to remember the name of an upscaler. I thought it was Glide XL or something.
GLID-3-XL?
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Waiting for Dall-e 2's release feels like waiting for a birthday gift.
I've been using the Glid-3 XL model. Here are some examples of what I've been able to do with it:
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Cyberpunk Anime Girl progressive enhancement
This was made with Glid-3 XL
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"Woah there, Dragonman!" (16 output images with CompVis latent diffusion)
The above notebooks use GitHub repo GLID-3-XL from Jack000. Regarding CLIP guidance, Jack000 states, "better adherence to prompt, much slower" (compared to classifier-free guidance).
glide-text2im
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인공지능에 대한 이해 : https://youtu.be/g1ARrNTwBHg 1편 - 딥러닝의 원리 https://youtu.be/CA5Ggqg5x6o 2편 - 인공지능의 창의성과 테슬라 AI https://youtu.be/jHYYggG7qq8 3편 - 코딩, 과학, 수학 난제를 해결하려는 A.I. https://youtu.be/BWJWAdMZGNY ---------------------------------------------------- 영상에 등장하는 링크 : ADOP(2021) https://arxiv.org
GLIDE(2021) https://syncedreview.com/2021/12/24/deepmind-podracer-tpu-based-rl-frameworks-deliver-exceptional-performance-at-low-cost-173/ || 소스코드 : https://github.com/openai/glide-text2im
- [R][P] I made an app for Instant Image/Text to 3D using PointE from OpenAI
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"Teacher villainess, DreamWorks official character design sheet turnaround, studio, Best on Artstation, 4K HD, by Nate Wragg"
The bolded part is a reference to the publicly released version of OpenAI's GLIDE, which is the predecessor of DALL-E 2. OpenAI didn't release the GLIDE model(s) trained on human faces.
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Trying to remember the name of an upscaler. I thought it was Glide XL or something.
OpenAI's GLIDE text2im https://github.com/openai/glide-text2im
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It just struck me that text diffs do *not* require the image-generating prompt as a starting point, and my mind is blown to pieces.
If I can stop wasting my time playing video games for a while, I might work on getting the Dalle-2 open-source predecessor (GLIDE) to work. Also can't wait for this to be released, I have so many uses for it!
- [D] Making text-to-image even better - GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models, a 5-minute paper summary by Casual GAN Papers
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Dall-E 2
A few comments by someone who's spent way too much time in the AI-generated space:
* I recommend reading the System Card that came with it because it's very through: https://github.com/openai/dalle-2-preview/blob/main/system-c...
* Unlike GPT-3, my read of this announcement is that OpenAI does not intend to commercialize it, and that access to the waitlist is indeed more for testing its limits (and as noted, commercializing it would make it much more likely lead to interesting legal precedent). Per the docs, access is very explicitly limited: (https://github.com/openai/dalle-2-preview/blob/main/system-c... )
* A few months ago, OpenAI released GLIDE ( https://github.com/openai/glide-text2im ) which uses a similar approach to AI image generation, but suspiciously never received a fun blog post like this one. The reason for that in retrospect may be "because we made it obsolete."
* The images in the announcement are still cherry-picked, which is therefore a good reason why they tested DALL-E 1 vs. DALL-E 2 presumably on non-cherrypicked images.
* Cherry-picking is relevant because AI image generation is still slow unless you do real shenanigans that likely compromise image quality, although OpenAI has likely a better infra to handle large models as they have demonstrated with GPT-3.
- Glide-Text2Im
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AI-generated photos of European flags
The flags were generated using Glide. You can try it out yourself in Google Colab
- New AI technique that lets you generate images from text. Now better than ever!
What are some alternatives?
latent-diffusion - High-Resolution Image Synthesis with Latent Diffusion Models
dalle-2-preview
dalle-flow - 🌊 A Human-in-the-Loop workflow for creating HD images from text
dalle-mini - DALL·E Mini - Generate images from a text prompt
dalle-playground - A playground to generate images from any text prompt using Stable Diffusion (past: using DALL-E Mini)
glide-text2im-colab - Colab notebook for openai/glide-text2im.
dalle-playground - A playground to generate images from any text prompt using DALL-E Mini and based on OpenAI's DALL-E https://openai.com/blog/dall-e/
pixray
meadowrun - Meadowrun makes it easy to run your code on the cloud
improved-diffusion - Release for Improved Denoising Diffusion Probabilistic Models
meadowrun-dallemini-demo - A demo of using Meadowrun to run DALL·E Mini, GLID3-XL, and SwinIR in an image generation pipeline
v-diffusion-pytorch - v objective diffusion inference code for PyTorch.