infery-examples
x-stable-diffusion
Our great sponsors
infery-examples | x-stable-diffusion | |
---|---|---|
1 | 5 | |
50 | 547 | |
- | -0.2% | |
0.0 | 4.5 | |
5 months ago | 5 months ago | |
Jupyter Notebook | Jupyter Notebook | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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.
infery-examples
x-stable-diffusion
-
[D] Is there an affordable way to host a diffusers Stable Diffusion model publicly on the Internet for "real-time"-inference? (CPU or Serverless GPU?)
Cheapest would be to deploy it on your own using: https://github.com/stochasticai/x-stable-diffusion. Let me if you need more help on real-time inference.
-
[D]deploy stable diffusion
However, I suggest you "accelerate" your inference first. For example, you can use open-source inference engines (see: https://github.com/stochasticai/x-stable-diffusion) to easily accelerate your inference 2x or more. That means you can generates 2x more images / $ on public clouds.
-
30% Faster than xformers? voltaML vs xformers stable diffusion - NVIDIA 4090
Brilliant, the x-stable-diffusion TensorRT/ AITemplate etc. sample image suggested they weren't consistent between the optimizations at all, unless they hadn't locked the seed which would have been foolish for the test.
-
Upto 2.5X speed up of Stable-diffusion/Dreambooth using one line of code with voltaML.
I was looking at this three days ago, the problem is there seems to be a huge difference in what is being generated looking at the example spread on https://github.com/stochasticai/x-stable-diffusion , whereas copying model, params, seed should be giving a near identical image.
- Using Tensor Cores for Deep Learning.
What are some alternatives?
tensorflow-onnx - Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
voltaML - ⚡VoltaML is a lightweight library to convert and run your ML/DL deep learning models in high performance inference runtimes like TensorRT, TorchScript, ONNX and TVM.
hand-gesture-recognition-mediapipe - This is a sample program that recognizes hand signs and finger gestures with a simple MLP using the detected key points. Handpose is estimated using MediaPipe.
AITemplate - AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore (NVIDIA GPU) and MatrixCore (AMD GPU) inference.
fastT5 - ⚡ boost inference speed of T5 models by 5x & reduce the model size by 3x.
sd_dreambooth_extension
nebuly - The user analytics platform for LLMs
jukebox - Code for the paper "Jukebox: A Generative Model for Music"
timm-flutter-pytorch-lite-blogpost - PyTorch at the Edge: Deploying Over 964 TIMM Models on Android with TorchScript and Flutter.
sdui - Local ImGui UI for Stable Diffusion. Features embedded PNG metadata, Apple M1 fixes, result caching, img2img, and more!
EdgeSAM - Official PyTorch implementation of "EdgeSAM: Prompt-In-the-Loop Distillation for On-Device Deployment of SAM"
stable-diffusion-webui - Stable Diffusion web UI