Finetuning does not have to be expensive! We put together a guide that discusses trade-offs between compute and time requirements.
Would love to hear other's experience in the responses 👇🏼
https://t.co/4tQoO4nkjF
Excited to announce the winner of our Stable diffusion challenge who won 100 Lightning credits (~147 GPU horus 🤯🤯🤯).
The challenge was to deploy a private stable diffusion API on Lightning AI Studios.
Praveen P's submission received the most likes.
In <2 minutes deploy a private stable diffusion API by clicking "open in Studio"
https://t.co/bUboESH4m0
It's great to see @LightningAI studios offering free GPU credits to users on a monthly basis.
But what are studios and why should you use one if you are working in AI?
Think about this scenario, you have built a machine learning project and want to share your code to the world.
If you use any of the existing ways to do this, most people will have to go through setting up the environment themselves and a lot more which causes a lot of friction.
With studios you can skip all of this, when someone replicates your studio the environment also gets replicated!
So the user can run the code directly without worrying about the overheads!
Here is one of the studios I launched last month -
https://t.co/1JNFmpP0WM