Stable Diffusion

Everything posted here must be related to AI. Note however that controllability is reduced compared to the 256x256 setting.

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. Stable Diffusion separates the image generating process into a diffusion process at runtime. Which is available on GitHub. Stable Diffusion is a state-of-the-art text-to-image art generation algorithm that uses a process called diffusion to generate images.

1 day agoStable DiffusionのDiscordに入れたので過去に製作されていた創造物をざらっと眺めてみました dream-1 dream-50をかなり見たそこでこれは基礎表現としてみんな知っておいた方がいいなという基礎的なPromptのみまとめます. Starting with only noise it gradually improves an image until there is no noise left at all. This will save each sample individually as well as a grid of size n_iter x n_samples at the specified output location default.

Stable Diffusion - News Art Updates. It is a breakthrough in speed and quality meaning that it can run on consumer GPUs. You can see some of the amazing output that has been created by this model without pre or post-processing on this page.

The Stable-Diffusion-v-1-4 checkpoint was initialized with the weights of the Stable-Diffusion-v-1-2 checkpoint and subsequently fine-tuned on 225k steps at resolution 512x512 on laion-aesthetics v2 5 and 10 dropping of the text-conditioning to. Welcome to the unofficial Stable Diffusion AI subreddit. 10 hours ago夜更かしをしていたらすごい勢いでStable Diffusionが落ちてきてあまりにうれしいのでこの喜びを皆様と分かち合いたく無償で公開します使い方低コスト運用ですのでテキストボックスに文字を入力したあとRequestボタンを押してしばらくしたらリロードしてみるとどこかに自分の.

We highly recommend that you share the prompt otherwise it is not required. Here you can post art discuss about the software share something cool you found etc. Stable Diffusion is an algorithm developed by Compvis the Computer Vision research group at Ludwig Maximilian University of Munich and sponsored primarily by Stability AI a startup that aims to.

Stable Diffusion is an open-source diffusion model for generating images from textual descriptions. Python scriptstxt2imgpy --prompt a sunset behind a mountain range vector image --ddim_eta 10 --n_samples 1 --n_iter 1 --H 384 --W 1024 --scale 50. StableDiffusion AI by the people for the people Community account.

I really hope this comes to google colab and we can do video diffusion the head honcho said it probably will and itll probably happen within a. Take everything you read here with a grain of salt. Diffusion works by training an artificial neural network to reverse a process of adding noise random pixels to an image.

7 hours agostable-diffusion-v1-4のリポジトリが既にあればその中で git switch fp16 でfloat16のモデルも取得するなどで半精度モデルを取得できないかなと考えています. Outputstxt2img-samplesQuality sampling speed and diversity are best controlled via the scale ddim_steps and ddim_eta arguments. As a rule of thumb higher values of scale produce better samples at the cost of a reduced output diversity.

Simulacrabot stablediffusion so awesome. Once trained the neural network can take an image made up of random pixels and turn it into an image that. High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach Andreas Blattmann Dominik Lorenz Patrick Esser Björn Ommer.

As these models were trained on image-text pairs from a broad internet scrape the model may reproduce some societal biases and produce unsafe content so open mitigation strategies as well as an open discussion about those biases can bring everyone to this conversation. Stable Diffusion is a text-to-image model that will empower billions of people to create stunning art within seconds. As of writing there is rapid development both on the software and user side.

Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. To create a sample of size 384x1024. Stable Diffusion was made possible thanks to a collaboration with Stability AI and Runway and builds upon our previous work.

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