K3ai is a lightweight infrastructure-in-a-box specifically built to install and configure AI tools and platforms to quickly experiment and/or run in production.
100 stars ⭐️⭐️⭐️⭐️⭐️⭐️ !
Thanks so much all!
Now we still looking for some help, unfortunately we have no time to improve @k3ai_project currently but we welcome your ideas!
Here's the @github link:
https://t.co/FDe5Xl0dKJ
The project maintainers: @bringyourownai@GSantomaggio
It's Friday so it's time for some nice add-on, how about @nvidia operator as a plugin?
Oh btw this works on @NVIDIAEmbedded Jetson using our arm version of @k3ai_project.
And don't forget to add a ⭐️ to our repo https://t.co/FDe5XkZFVb pretty please!
#ai#mlops#datascience#edge
@AlexandreBrown0 2/2 problem I see is minio. But if Kubeflow is already installed I can redirect the MLFlow installation to "re-use" the KF minio installation.
@GithubProjects how about us? @k3ai_project is a simple CLI to start your ML experimentation without the complexity of learn how to the setup the entire AI stack.
https://t.co/LwxQfqKjg6
@MatejKorvin@kubeflow thanks, I still have to fix a few things..like checking the ARM real list of platforms and adding back the GPU support plus FPGA and other stuff...
Anyone want to run a pipeline in less than 3 steps? Let me rephrase: 1) install a K8s cluster
2) install @kubeflow pipelines
3) run your pipeline
Not yet convinced, check our docs with our new v1.0.1 version:
https://t.co/sysXGVI0HI
@AlexandreBrown0 Yes you may customize the cluster config using the extras for kubeflow you may install the single components (later will create the bundles) .. if you may open some issues on this we will be super happy to follow up!
So while we are busy working on v1.0.1 of K3ai (https://t.co/Sd47iPS2XW) we wanted to share a short preview of running @MLflow on top of K8s all within an #arm64 . I hope you'll don't mind to add a ⭐ to k3ai https://t.co/8tLTJG8oxV
Check the video: https://t.co/K4bH8xrKYT
Some new plugins are coming in v1.0.1 curious ? Here a sneak preview @rubrixml fully supported within @kubernetesio with @elastic
If you want to contribute add a ⭐ to our @github repo : https://t.co/8tLTJG8oxV
Release date for v1.0.1: November 30th
Should I say @civo and @VMwareTanzu are ready? Should I say deploy #Kubernetes#ai tools and the code in one single command?
V1.0.1 is one week away and will be awesome !!!!
K3ai - Running @kubeflow pipelines with one click - Simple as: write your code in @GitHub (even in a folder of your repo)-->run "k3ai run ..." and we will take care of everything:
https://t.co/MxJTsDajU1 via @YouTube
Add a ⭐ to the project https://t.co/8tLTJG8oxV
K3ai - Running @kubeflow pipelines with one click - Simple as: write your code in @GitHub (even in a folder of your repo)-->run "k3ai run ..." and we will take care of everything:
https://t.co/MxJTsDajU1 via @YouTube
Add a ⭐ to the project https://t.co/8tLTJG8oxV
Are you on #Windows11 ? Do you have @Docker and #WSL installed?
Open #WSL :
1) curl -sfL https://t.co/Y4juEbZIHz | sh -
2) k3ai up
3) k3ai cluster deploy -t k3d -n mycluster --extras "--gpus=all"
4) k3ai plugin deploy -n mlflow -t mycluster
you are welcome ;)