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Based on our record, Banana.dev seems to be a lot more popular than Label Studio. While we know about 13 links to Banana.dev, we've tracked only 1 mention of Label Studio. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
If instead you have a cohort on hand — -i.e., you do not want to send your data to a third party for any reason, or perhaps you have energetic undergrads — -then you could alternatively consider local, open-source annotation such as CVAT and Label Studio. Finally, nowadays, you might instead work with Large Multimodal Models to have them annotate your data; more on this awkward angle later. - Source: dev.to / 2 months ago
For the inference part, you can dockerise your model and use https://banana.dev for serverless GPU. They have examples on github on how to deploy and I’ve done it last year and was pretty straightforward. - Source: Hacker News / 2 months ago
I want to first check the user's ID and only if the user has an active subscription then the request will be forwarded to my API on banana.dev else the request will be blocked at the middleware itself. Should I use Express JS for the middleware i.e. Authentication and forwarding requests? Is there any other better way to improve my project structure? Currently it looks like:. Source: 7 months ago
Hey! Would love to have you try https://banana.dev (bias: I'm one of the founders). We run A100s for you and scale 0->1->n->0 on demand, so you only pay for what you use. I'm at erik@banana.dev if you want any help with it :). - Source: Hacker News / about 1 year ago
CAN you do this in AWS? Of course, do they have a service that does exactly what this banana.dev does? Probably not. Source: about 1 year ago
I've been using banana.dev for easily running my ML models on GPU in a serverless manner, and interacting with them as an API. Although the principle of the service is sound, it is currently too buggy to take into production (very long cold boots, errorring requests, always hitting capacity). Source: about 1 year ago
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mlblocks - A no-code Machine Learning solution. Made by teenagers.