linux
stable-diffusion
linux | stable-diffusion | |
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30 | 382 | |
2,100 | 65,504 | |
1.8% | 1.1% | |
0.0 | 0.0 | |
7 days ago | 21 days ago | |
C | Jupyter Notebook | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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.
linux
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Red Hat to Author New Linux Driver for Nvidia GPUs in Rust
You're missing on a lot of things Rust (or any language with non-toy types) can provide. Lock ordering, better accessible complex structures, enforcement of enumerated options, rich description of APIs, and many others. Atomic values are usable transparently https://github.com/AsahiLinux/linux/blob/97c628055904a7f2ef1... and multithreaded reference counting is easily enforced https://github.com/AsahiLinux/linux/blob/bd0a1a7d465fcb60685... also issues like type confusion https://www.vicarius.io/vsociety/posts/a-type-confusion-bug-... are less likely if you can easily use tagged unions checked by the compiler.
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Asahi Linux project's OpenGL support on Apple Silicon officially surpasses Apple
From the gpu issue tracker[0]:
> For a bit of context -- Google Maps loads images to the GPU at.. inopportune times. While games would typically load their images during a load screen (so slow image loading just means longer loading screens), Google Maps loads when scrolling around I think (so slow image loading means the whole map stutters). I don't think there's a fundamental driver bug we can fix here, but we can make image loading a lot faster which makes the symptoms go away.
[0]: https://github.com/AsahiLinux/linux/issues/72#issuecomment-1...
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Committing to Rust for Kernel Code
> Is this mostly just a thing to get more young people interested in kernel development...allowing them to start out in less important areas and in a language they are passionate about?
Not likely. At the moment you need to do extra work to get Rust working well. It's not exactly beginner friendly and doing work in the kernel, you'll need to dig into C anyway.
> Or is this a serious proposal about the future of operating systems and other low level infrastructure code?
Serious code already exists, so... Yes?
> Do you just program everything in unsafe mode? What about runtimes?
Why would you? You need that only when interfacing with something that can't hold the Rust compiler assumptions. See for example https://github.com/AsahiLinux/linux/blob/gpu/rebase-6.4/driv...
The few places that need direct access / unsafe are almost all single-line areas with an explanation.
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Speaker Support in Asahi Linux
I think the idea with the M-series laptops in particular is that you can drive the speakers at volumes that actually damage them very quickly ( see https://github.com/AsahiLinux/linux/issues/53 ). The idea AIUI is that you can use a DSP along with a physical model of the voice coil to get better sound than you would if the speakers were volume-limited.
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Ask HN: How is Rust used in the Linux kernel today?
I am using Asahi Linux and the GPU driver works great, it even supports OpenGL 3.1 (https://asahilinux.org/2023/06/opengl-3-1-on-asahi-linux/). Definitely not alpha, I would say it's close to a "release candidate". Many bugs got resolved, nothing much left (besides newer OpenGL and Vulkan of course, but current state is very stable): https://github.com/AsahiLinux/linux/issues/72
- Charging Threshold for Gnome Asahi Linux users
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The Linux Kernel Module Programming Guide
There aren't really any non-trivial mainline modules, since the Rust support is so new. There's the non-mainline Asahi M1 GPU driver though! It will eventually be mainlined, but IIRC some more Rust support code needs to be mainlined first.
https://github.com/AsahiLinux/linux/tree/asahi/drivers/gpu/d...
- Asahi Linux: Initial Apple M2 Pro/Max device trees and early support added to the Linux kernel (bringup)
- Initial M2 Pro/Max device trees and early support added to m1n1 and Linux kernel
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Fix Asahi Linux Screen Temperature?
You can follow the progress here: https://github.com/AsahiLinux/linux/issues/91
stable-diffusion
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Go is bigger than crab!
Which is a 1-click install of Stable Diffusion with an alternative web interface. You can choose a different approach but this one is pretty simple and I am new to this stuff.
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Why & How to check Invisible Watermark
an invisible watermarking of the outputs, to help viewers identify the images as machine-generated.
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How to create an Image generating AI?
It sounds like you just want to set up Stable Diffusion to run locally. I don't think your computer's specs will be able to do it. You need a graphics card with a decent amount of VRAM. Stable diffusion is in Python as is almost every AI open source project I've seen. If you can get your hands on a system with an Nvidia RTX card with as much VRAM as possible, you're in business. I have an RTX 3060 with 12 gigs of VRAM and I can run stable diffusion and a whole variety of open source LLMs as well as other projects like face swap, Roop, tortoise TTS, sadtalker, etc...
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Two video cards...one dedicated to Stable Diffusion...the other for everything else on my PC?
Use specific GPU on multi GPU systems · Issue #87 · CompVis/stable-diffusion · GitHub
- Automatic1111 - Multiple GPUs
- Ist Google inzwischen einfach unbrauchbar?
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Why are people so against compensation for artists?
I dealt with this in one of my posts. At least SD 1.1 till 1.5 are all trained on a batch size of 2048. The version pretty much everyone uses (1.5) is first pretrained at a resolution of 256x256 for 237K steps on laion2B-en, at the end of those training steps it will have seen roughly 500M images in laion2B-en. After that it is pre-trained for 194K steps on laion-high-resolution at a resolution of 512x512, which is a subset of 170M images from laion5B. Finally it is trained for 1.110K steps on LAION aesthetic v2 5+. This is easily verified by taking a glance at the model card of SD 1.5. Though that one doesn't specify for part of the training exactly which aesthetic set was used for part of the training, for that you have to look at the CompVis github repo. Thus at the end of it all both the most recent images and the majority of images will have come from LAION aesthetic v2 5+ (seeing every image approx 4 times). Realistically a lot of the weights obtained from pretraining on 2B will have been lost, and only provided a good starting point for the weights.
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Is SDXL really open-source?
stable diffusion · CompVis/stable-diffusion@2ff270f · GitHub
- I want to ask the AI to draw me as a Pokemon anime character then draw six of Pokemon of my choice next to me. What are my best free, 15$ or under and 30$ or under choices?
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how can i create my own ai image model
Here for example --> https://github.com/CompVis/stable-diffusion
What are some alternatives?
Amethyst - Automatic tiling window manager for macOS à la xmonad.
GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
fritter - A privacy-friendly Twitter frontend for mobile devices
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
linux-m1 - Linux kernel source tree
diffusers-uncensored - Uncensored fork of diffusers
docs - Hardware and software docs / wiki
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
ExpansionCards - Reference designs and documentation to create Expansion Cards for the Framework Laptop
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
nomicon - The Dark Arts of Advanced and Unsafe Rust Programming
onnx - Open standard for machine learning interoperability