generative-models
artbot-for-stable-diffusion
generative-models | artbot-for-stable-diffusion | |
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21 | 85 | |
22,649 | 161 | |
4.4% | - | |
7.3 | 9.4 | |
about 1 month ago | 2 months ago | |
Python | TypeScript | |
MIT License | MIT License |
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generative-models
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Creating Videos with Stable Video Diffusion
git clone https://github.com/Stability-AI/generative-models.git && cd generative-models
- Show HN: I have created a free text-to-image website that supports SDXL Turbo
- How To Increase Performance Time on MacOS
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Introducing Stable Video Diffusion: Stability AI's New AI Research Tool for Image-to-Video Synthesis
Generative Models by Stability AI Github Repository
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image-to-video tutorial
# clone SD repo !git clone https://github.com/Stability-AI/generative-models.git # cd into working directory # the % sets the pwd globally as usually each command is run in a subshell in google colab %cd /content/generative-models/ # installing dependencies !pip install -r requirements/pt2.txt !pip install . # HACK # I was getting ModuleNotFoundError: No module named 'scripts' # This is what ChatGPT suggested (let me know if there is a better way) file_path = '/content/generative-models/scripts/sampling/simple_video_sample.py' new_text = "import sys\nsys.path.append('/content/generative-models')\n\n" with open(file_path, 'r') as file: original_content = file.read() updated_content = new_text + original_content with open(file_path, 'w') as file: file.write(updated_content) # Need to create a checkpoints/ folder - that is where the system looks for weights import os dir_name = 'checkpoints' if not os.path.exists(dir_name): os.makedirs(dir_name) print(f"Directory '{dir_name}' created") else: print(f"Directory '{dir_name}' already exists") # Download weights into checkpoints/ folder from huggingface_hub import hf_hub_download hf_hub_download(repo_id="stabilityai/stable-video-diffusion-img2vid", filename="svd.safetensors", local_dir="checkpoints", local_dir_use_symlinks=False) # I can't remember if this step is needed but it aims to reduce the memory footprint of pytorch # I kept getting CUDA out of memory # I got these instructions from the out of memory error message os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'max_split_size_mb:512' print(os.environ['PYTORCH_CUDA_ALLOC_CONF']) # Inside of scripts/sampling/simple_video_sample.py you need to make 2 updates 1. input_path (line 26): update to the location of your file (I attached Gdrive so mine was "/content/drive/MyDrive/examples/car.jpeg" 2. decoding_t (line 34): update it to 5. you need to do this for memory preservation (CUDA out of memory). I'm not sure if 5 is the best value but it worked for me # Finally generate the video (output will be in the outputs/ folder) !python scripts/sampling/simple_video_sample.py
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Stable Video Diffusion
It looks like the huggingface page links their github that seems to have python scripts to run these: https://github.com/Stability-AI/generative-models
- GitHub - Stability-AI/generative-models: Generative Models by Stability AI
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How does ComfyUI load SDXL 1.0 so VRAM-efficiently? How do I do the same in vanilla python code?
However, when using the example code from HuggingFace or setting up stuff from the StabilityAI/generative-models repo in a jupyter notebook, I end up using 21 GB of VRAM just for running the default pipeline (with no base model output). If I try to run the extra `base.vae.decode(base_latents)` after generation to get unrefined outputs, I get a CUDA out of memory error as it blows past the 24GB of my NVIDIA RTX 3090.
- SDXL 1.0 is out!
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SDXL 0.9 Anyone having luck NOT centering subjects?
SDXL uses cropping information as part of the conditioning. Images were randomly cropped during training and the coordinates of the crop were included as two integers at the end of the conditioning vector. If you're using ComfyUI you can use the CLIPTextEncodeSDXL node to specify where the upper left corner of the image should appear to be in relation to some hypothetical uncropped image. Here's a figure with examples from the report on SDXL:
artbot-for-stable-diffusion
- ArtBot for Stable Diffusion
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Show HN: I have created a free text-to-image website that supports SDXL Turbo
I am going to plug artbot, an actually free SD image generator: https://tinybots.net/artbot
The front end is all local, and the backend image generation run on volunteer hosts running on the AI Hoard. I donate my own 3090/2060 sometimes (albeit for text generation, not imagegen).
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NSFW AI Tools
No mention of the AI Horde anywhere?
https://tinybots.net/artbot
https://lite.koboldai.net/
- Run LLMs at home, BitTorrent‑style
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Stability AI releases its latest image-generating model, Stable Diffusion XL 1.0
This AI Horde UI has, IMO, some really good templates and suggestions:
https://tinybots.net/artbot
- SDXL 1.0 Release Candidate now in rotation on the AI Horde
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A prompt without a subject!
Tried just now and this is the result, i haven't clear what is the LSDR 3.75 parameter, im using https://tinybots.net/artbot
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[DISCUSSION] The delegitimization of AI art is nothing new...
Try either of these, they in theory would work on your phone or PC https://aqualxx.github.io/stable-ui/ https://tinybots.net/artbot
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Useful Links
ArtBot
- Sci-Fi posters
What are some alternatives?
background-removal-js - Remove backgrounds from images directly in the browser environment with ease and no additional costs or privacy concerns. Explore an interactive demo.
unprompted - Templating language written for Stable Diffusion workflows. Available as an extension for the Automatic1111 WebUI.
wizmap - Explore and interpret large embeddings in your browser with interactive visualization! đź“Ť
civitai - A repository of models, textual inversions, and more
evernote-ai-chatbot
ControlNet - Let us control diffusion models!
gping - Ping, but with a graph
A1111-Web-UI-Installer - Complete installer for Automatic1111's infamous Stable Diffusion WebUI
graphic-walker - An open source alternative to Tableau. Embeddable visual analytic
scribble-diffusion - Turn your rough sketch into a refined image using AI
xgen - Salesforce open-source LLMs with 8k sequence length.
stable-diffusion-webui-colab - stable diffusion webui colab