tabular-dl-pretrain-objectives
Revisiting Pretrarining Objectives for Tabular Deep Learning (by puhsu)
latent-diffusion
High-Resolution Image Synthesis with Latent Diffusion Models (by CompVis)
| tabular-dl-pretrain-objectives | latent-diffusion | |
|---|---|---|
| 1 | 70 | |
| 58 | 10,726 | |
| - | 3.7% | |
| 10.0 | 0.0 | |
| over 1 year ago | 3 months ago | |
| Python | Jupyter Notebook | |
| - | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tabular-dl-pretrain-objectives
Posts with mentions or reviews of tabular-dl-pretrain-objectives.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-03.
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[D] Influential papers round-up 2022. What are your favorites?
Found relevant code at https://github.com/puhsu/tabular-dl-pretrain-objectives + all code implementations here
latent-diffusion
Posts with mentions or reviews of latent-diffusion.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-21.
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SDXL: The next generation of Stable Diffusion models for text-to-image synthesis
Stable Diffusion XL (SDXL) is the latest text-to-image generation model developed by Stability AI, based on the latent diffusion techniques. SDXL has the potential to create highly realistic images for media, entertainment, education, and industry domains, opening new ways in practical uses of AI imagery.
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Is it possible to create a checkpoint from scratch?
Here's a link to the early latent-diffusion git, that might be able to create a blank model (I haven't tested it): https://github.com/CompVis/latent-diffusion
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Anything better than pix2pixHD?
Latent diffusion could work for you: https://github.com/CompVis/latent-diffusion (https://arxiv.org/abs/2112.10752)
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Image Upscaler AI
There are a lot but the one implemented as LDSR in most stable guis is this one. https://github.com/CompVis/latent-diffusion
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I've been collecting millions of images of only public domain /cc0 licensing. I'd like to train a stable diffusion model on the collection. Could some one share their knowledge of what this would take? Otherwise, simply enjoy my library.
CompVis/latent-diffusion: High-Resolution Image Synthesis with Latent Diffusion Models (github.com)
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Run Clip on iPhone to Search Photos
The "retrieval based model" refers to https://github.com/CompVis/latent-diffusion#retrieval-augmen..., which uses ScaNN to train a knn embedding searcher.
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Class Action Lawsuit filed against Stable Diffusion and Midjourney.
Stability is basically https://github.com/CompVis/latent-diffusion + training data.
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[D] Influential papers round-up 2022. What are your favorites?
Found relevant code at https://github.com/CompVis/latent-diffusion + all code implementations here
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Can anyone explain differences between sampling methods and their uses to me in simple terms, because all the info I've found so far is either very contradicting or complex and goes over my head
DDIM and PLMS were the original samplers. They were part of Latent Diffusion's repository. They stand for the papers that introduced them, Denoising Diffusion Implicit Models and Pseudo Numerical Methods for Diffusion Models on Manifolds.
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AI art is very dystopian.
yes, https://github.com/CompVis/latent-diffusion
What are some alternatives?
When comparing tabular-dl-pretrain-objectives and latent-diffusion you can also consider the following projects:
Swin-Transformer - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
disco-diffusion
tabular-dl-tabr - The implementation of "TabR: Unlocking the Power of Retrieval-Augmented Tabular Deep Learning"
dalle-mini - DALL·E Mini - Generate images from a text prompt
MTR - The official implementation of the paper "Rethinking Data Augmentation for Tabular Data in Deep Learning"
hent-AI - Automation of censor bar detection
dalle-2-preview
stable-diffusion
DALLE2-pytorch - Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
stable-diffusion - A latent text-to-image diffusion model
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
tabular-dl-pretrain-objectives vs Swin-Transformer
latent-diffusion vs disco-diffusion
tabular-dl-pretrain-objectives vs tabular-dl-tabr
latent-diffusion vs dalle-mini
tabular-dl-pretrain-objectives vs MTR
latent-diffusion vs hent-AI
latent-diffusion vs dalle-2-preview
latent-diffusion vs stable-diffusion
latent-diffusion vs DALLE2-pytorch
latent-diffusion vs stable-diffusion
latent-diffusion vs VQGAN-CLIP
latent-diffusion vs CLIP