ml-stable-diffusion
aws-node-termination-handler
ml-stable-diffusion | aws-node-termination-handler | |
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45 | 94 | |
16,111 | 1,567 | |
0.7% | 1.0% | |
7.4 | 8.0 | |
26 days ago | 3 days ago | |
Python | Go | |
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.
ml-stable-diffusion
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Show HN: Run Stable Diffusion Directly on iPhone
Not sure how that got in here. Apple released CoreML Stable Diffusion library a little over a year ago [1]. Hugging Face released their version of the example app for the CoreML Stable Diffusion library [2].
The app should be able to run on iPhone 14 Pro, I believe the requirements is about 6-8Gb of RAM. And I was not able to run it on iPhone 13 Mini, because it has only 4Gb of RAM.
- [1] https://github.com/apple/ml-stable-diffusion
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Apple releases MLX; has working Stable Diffusion example
Where are you seeing a Stable Diffusion example? I'm familiar with Apple's CoreML Implementation of StableDiffusion, but is there something else in the SD world available for download now as part of MLX?
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Stable Diffusion XL on iPhone with Core ML
Other features and improvements to the repo https://github.com/apple/ml-stable-diffusion
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FLaNK Stack Weekly for 20 June 2023
M1! https://github.com/apple/ml-stable-diffusion
- Apple Introduces M2 Ultra with up to 192GB Unified Memory - LLM powerhouse?
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Need help choosing between two laptops
M2 MBA can run Stable Diffusion and LLaMa comfortably, which means generating your potential game/image asset locally. They're pretty much impractical in 7340.
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Speed Is All You Need: On-Device Acceleration of Large Diffusion Models
Interestingly these are OpenCL kernels so in theory some of the optimizations might run out-of-the-box on CPUs.
It would be instructive to compare their speedups on the iPhone to the Apple CoreML implementation: https://github.com/apple/ml-stable-diffusion
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Is it worth buying a used M1 Mac for stable diffusion when you have iPad M1 but Intel Mac
Stable Diffusion runs great on my M1 Macs. The Draw Things app makes it really easy to run too. You also can’t disregard that Apple’s M chips actually have dedicated neural processing for ML/AI. This actual makes a Mac more affordable in this category because you don’t need to purchase a beefy graphics card. Not to mention that Apple has even optimized their software specifically for Stable Diffusion (related GitHub). Draw Things can take advantage of this. There’s a few guides to running the web UI on M1 too. I prefer the Draw Things app because of how easy it is to use, but the web UI is also nice because of all of the plugins and workflows that the community has built over time.
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Stable diffusion for Apple silicon
LINKS: ml-stable-diffusion: https://github.com/apple/ml-stable-diffusion Diffusers (HuggingFace Mac App): https://apps.apple.com/app/diffusers/id1666309574?mt=12
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Apple: Transformer architecture optimized for Apple Silicon
So, is Stable Diffusion working finally on TPU or not? DiffusionBee uses GPU and running this https://github.com/apple/ml-stable-diffusion with CPU_AND_NE just segfaults
aws-node-termination-handler
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Disaster Recovery Strategies for EC2 Deployments
Disaster recovery is a critical component of any IT infrastructure. It ensures that your applications and data are protected in the event of an unexpected outage or disaster. In this blog post, we will explore different disaster recovery strategies for Amazon Elastic Compute Cloud (EC2) deployments.
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Compliant infrastructure using infrastructure as code
When you are using compute you have a lot of options. One of these options is Amazon EC2. In a world where more and more workloads become serverless. You might still have this use-case that is better off on EC2. But, how do you combine EC2 with compliance and security? In this blog post we will explore how we can build a compliant and secure EC2 stack.
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Hosting an Angular application in a Docker container on Amazon EC2 deployed by Amazon ECS
In this article, a WEB application using the latest version of Angular in a built Docker image will be hosted on Amazon EC2 (Elastic Compute Cloud) and deployed by Amazon ECS (Elastic Container Service) using an Amazon ECR (Elastic Container Registry) containers repository.
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The 2024 Web Hosting Report
The single most important development in hosting since the invention of EC2 is defined by its own 3-letter acronym: k8s. Kubernetes has won the “container orchestrator” space, becoming the default way that teams across industries are managing their compute nodes and scheduling their workloads, from data pipelines to web services.
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Minecraft Server on AWS
EC2
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Starting My AWS Certification Journey as a Certified Cloud Practitioner
Then in 2020, I started working with AWS. My first two years with AWS were mostly interacting with the Node.js apps I've deployed in EC2 and reviewing logs since we had a DevOps engineer who managed the cloud infrastructure.
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Choosing the Right AWS EC2 Instance: Avoiding Common Pitfalls
If you want to learn more about EC2 and get detailed information, I suggest you start your journey by visiting https://aws.amazon.com/ec2/. This is the best place to begin learning about EC2.
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Why should tech beginners learn Cloud Computing?
AWS - Cloud Computing AWS - EC2 Wikipedia - Cloud Computing Guru99 - Cloud Computing Cloudflare - Cloud Computing Cloudzero - Statistics Zippia - Statistics
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Authenticating users in the load balancer with Cognito
Say that we have an application running behind a public-facing Application Load Balancer (ALB). The load balancer's target can be any supported target, including ECS containers, EC2 instances or even Lambda functions. Because the application is only available to authenticated users, we want to find a solution to identify them.
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Programmatically retrieving secrets from Parameter Store and Secrets Manager
Although I'll use Lambda functions in the examples, we can transfer the concepts to other compute resources, like EC2 instances, and ECS or EKS containers.
What are some alternatives?
MochiDiffusion - Run Stable Diffusion on Mac natively
terraform - Terraform enables you to safely and predictably create, change, and improve infrastructure. It is a source-available tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned.
ml-ane-transformers - Reference implementation of the Transformer architecture optimized for Apple Neural Engine (ANE)
kops - Kubernetes Operations (kOps) - Production Grade k8s Installation, Upgrades and Management
modelscope - ModelScope: bring the notion of Model-as-a-Service to life.
autoscaler - Autoscaling components for Kubernetes
pulsar-recipes - A StreamNative library containing a collection of recipes that are implemented on top of the Pulsar client to provide higher-level functionality closer to the application domain.
k3s-aws-terraform-cluster - Deploy an high available K3s cluster on Amazon AWS
fast-stable-diffusion - fast-stable-diffusion + DreamBooth
Plausible Analytics - Simple, open source, lightweight (< 1 KB) and privacy-friendly web analytics alternative to Google Analytics.
stable-diffusion-webui - Stable Diffusion web UI
amazon-ec2-metadata-mock - A tool to simulate Amazon EC2 instance metadata