stable-diffusion-cpu
openvino
stable-diffusion-cpu | openvino | |
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4 | 17 | |
68 | 6,028 | |
- | 4.9% | |
0.0 | 10.0 | |
about 1 year ago | about 24 hours ago | |
Jupyter Notebook | C++ | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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stable-diffusion-cpu
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Pocket Dragons - Coffee with your pet Dragon
Created with stable-diffusion-cpu on an HP Proliant server, CPU-only, dual Xeon, 16c/32t.
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Run Stable Diffusion on Intel CPUs
I found this repo early on and have been using it to run inference on my M1 Pro MBP. https://github.com/ModeratePrawn/stable-diffusion-cpu
For me it runs at about 3.5 seconds per iteration per picture at 512x512.
There is also a fork that uses metal here and is much faster: https://github.com/magnusviri/stable-diffusion/tree/apple-si...
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StableDiffusion RUNS on M1 chips.
Download the code from the Github repo https://github.com/ModeratePrawn/stable-diffusion-cpu and unzip it. Open it on an editor (e.g. VS Code)
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The Stable Diffusion wiki guide does not work for Mac, however the guide does not state this.
For CPU, try: https://github.com/ModeratePrawn/stable-diffusion-cpu
openvino
- FLaNK Stack 05 Feb 2024
- QUIK is a method for quantizing LLM post-training weights to 4 bit precision
- Intel OpenVINO 2023.1.0 released
- Intel OpenVINO 2023.1.0 released, open-source toolkit for optimizing and deploying AI inference
- OpenVINO 2023.1.0 released
- [N] Intel OpenVINO 2023.1.0 released, open-source toolkit for optimizing and deploying AI inference
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Powering Anomaly Detection for Industry 4.0
Anomalib is an open-source deep learning library developed by Intel that makes it easy to benchmark different anomaly detection algorithms on both public and custom datasets, all by simply modifying a config file. As the largest public collection of anomaly detection algorithms and datasets, it has a strong focus on image-based anomaly detection. It’s a comprehensive, end-to-end solution that includes cutting-edge algorithms, relevant evaluation methods, prediction visualizations, hyperparameter optimization, and inference deployment code with Intel’s OpenVINO Toolkit.
What are some alternatives?
stable-diffusion-amd
TensorRT - NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
stable_diffusion.openvino
deepsparse - Sparsity-aware deep learning inference runtime for CPUs
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
rocm-gfx803
stable-diffusion - Go to lstein/stable-diffusion for all the best stuff and a stable release. This repository is my testing ground and it's very likely that I've done something that will break it.
neural-compressor - SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime
txt2imghd - A port of GOBIG for Stable Diffusion
nebuly - The user analytics platform for LLMs