diffusers VS diffusionbee-stable-diffusion-ui

# Step 1: Install required packages pip install transformers>=4.51.3 pip install git+https://github.com/huggingface/diffusers pip install python-pptx torch pillow # Step 2: Verify CUDA availability (for GPU users) python -c "import torch; print(torch.cuda.is_available())"

Diffusers Documentation

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 pip install einops timm pillow pip install git+https://github.com/huggingface/transformers pip install git+https://github.com/huggingface/accelerate pip install git+https://github.com/huggingface/diffusers pip install huggingface_hub pip install sentencepiece bitsandbytes protobuf decord numpy

System requirements: 24GB GPU memory and 64GB+ RAM > pip install git+https://github.com/huggingface/diffusers

pip install --upgrade pip pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 pip install git+https://github.com/huggingface/diffusers.git pip install transformers accelerate safetensors numpy pillow

I'm not a fan of Python, but it is the languange of choice for most Machine Learning code. I'm currently working on a NodeJS based project where I need to call the HuggingFace Diffusers python module. So I came up with an IPC wrapper around the the Python script.

!pip install torch torchvision torchaudio einops timm pillow !pip install git+https://github.com/huggingface/transformers !pip install git+https://github.com/huggingface/accelerate !pip install git+https://github.com/huggingface/diffusers !pip install huggingface_hub !pip install sentencepiece bitsandbytes protobuf decord ffmpeg-python imageio opencv-python

> All the self-hosted LLM and text-to-image models come with some restrictions trained into them

https://github.com/huggingface/diffusers/issues/3422

import modal image = modal.Image.debian_slim(python_version="3.10").apt_install( "libglib2.0-0", "libsm6", "libxrender1", "libxext6", "ffmpeg", "libgl1", "git" ).pip_install( "git+https://github.com/huggingface/diffusers.git", "invisible_watermark", "transformers", "accelerate", "safetensors", "sentencepiece", )

pip install torch==2.3.1 pip install git+https://github.com/huggingface/diffusers.git pip install transformers==4.43.3 sentencepiece==0.2.0 accelerate==0.33.0 protobuf==5

I usually don't want to comment on these, but: DiffusionBee's repo https://github.com/divamgupta/diffusionbee-stable-diffusion-... don't have any updates for 9 months except regular binary releases. There is no source code available for their recent builds. I think it is a bit unfair to say it is open-source app at this point given you are using a binary probably far different from the repo.

Try Diffusion Bee's latest release https://github.com/divamgupta/diffusionbee-stable-diffusion-...

* LLaVA model: I'll add more documentation. You are right Llava could not generate images. For image generation I don't have immediate plans, but checkout these projects for local image generation.

- https://diffusionbee.com/

- https://github.com/comfyanonymous/ComfyUI

- https://github.com/AUTOMATIC1111/stable-diffusion-webui

Interesting, will check it out to see how it compares with https://diffusionbee.com which I am using for last few months for fun.

It depends on what you are planning to do. Stable diffusion works great locally on both the dell+linux and the mac laptop I tried it on. This one was easy to use while exploring models from huggingface: https://diffusionbee.com/

diffusion bee is the easiest app to use.

If you have a Mac, I highly recommend DiffusionBee. It’s an app you can install on your computer and use as much as you want (even offline) for free. The website has older downloads but if you go here you can get the latest beta with more features: https://github.com/divamgupta/diffusionbee-stable-diffusion-ui/releases

Try these first: 1. https://drawthings.ai/ 2. https://diffusionbee.com/