DALL-E
PyTorch package for the discrete VAE used for DALL·E. (by openai)
deep-vector-quantization
VQVAEs, GumbelSoftmaxes and friends (by karpathy)
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DALL-E | deep-vector-quantization | |
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31 | 2 | |
10,709 | 463 | |
0.3% | - | |
0.0 | 0.0 | |
3 months ago | over 2 years ago | |
Python | Jupyter Notebook | |
GNU General Public License v3.0 or later | 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.
DALL-E
Posts with mentions or reviews of DALL-E.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-06-25.
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Issue installing DALL-E
Not sure if this is the right place to post this but I'm having an issue installing DALL-E from github. I'm using this video as a tutorial and downloaded the DALL-E file from here. I got the the part of setting up a docker thing to run it but I'm getting the error shown in this picture:
- is dall e programmed? If yes how?
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small chungus
well part of it is: https://github.com/openai/DALL-E
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How to run DALL-E locally?
Following the read me, I ran
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Error message "File cannot be written" on Linux Endeavour
I am trying to run a program from GitHUb (Dall-E; https://github.com/openai/dall-e). My first step was to run pip install DALL-E in the Terminal, which worked fine.
- lofi nuclear war to relax and study to
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[N] [D] Openai, who runs DALLE-2 alleged threatened creator of DALLE-Mini
Code for https://arxiv.org/abs/2102.12092 found: https://github.com/openai/DALL-E
- A music-video generated by AI #Dalle2
- Dall-E - Pytorch package for the discrete vae used for dall·e.
- Created this with AI painting software
deep-vector-quantization
Posts with mentions or reviews of deep-vector-quantization.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-09-08.
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[D] Intuition about "Discrete Latents" in paper about VQ-VAEs
How the codebook is initialised makes a big difference, if more codes are used at the start then they often stay in use but it can be finicky to figure that out. I've found initialising codes normally with small standard deviation (e.g. 0.01) to help (so codes lie on a hypersphere). Failing that, here is an example with k-means initialisation https://github.com/karpathy/deep-vector-quantization .
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this is not overfitting but something else, right?
The context is, that I am trying to learn a discrete vocabulary of latent codes, i.e. have a discrete learnable embedding to sort of quantize the otherwise continuous latent outputs of the encoder that are then used to reconstruct the input image via the decoder cf. this code snippet. So the idea is not to generate random sampled from noise but to learn an efficient notebook, i.e. bottleneck that captures the essentials of the data set. The decoder then outputs a prob distribution for every pixel over the 255 possible values 8 bit images can take o. The KL (assuming a uniform prior to encourage uniform use of all possible vocabulary entries) is currently weighted with 1.
What are some alternatives?
When comparing DALL-E and deep-vector-quantization you can also consider the following projects:
dalle-2-preview
chainer-VQ-VAE - A Chainer implementation of VQ-VAE.
DALLE-pytorch - Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
DALLE2-pytorch - Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
big-sleep - A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN. Technique was originally created by https://twitter.com/advadnoun
pixray
dalle-mini - DALL·E Mini - Generate images from a text prompt
gpt-3 - GPT-3: Language Models are Few-Shot Learners
DallEval - DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation Models (ICCV 2023)