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CakePHP
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Based on our record, Lambda Face Recognition API should be more popular than CakePHP. It has been mentiond 27 times since March 2021. 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.
CakePHP is an open-source PHP web framework designed to help developers build web applications quickly. It is based on the MVC (Model-View-Controller) architecture and provides a powerful toolkit to simplify common development tasks such as database interactions, form handling, authentication, and session management. - Source: dev.to / about 2 years ago
CakePHP is an open-source PHP framework for web development with 8.7k stars and 3.5k forks on GitHub. It offers APIs that enable developers to develop applications quickly. It allows you to create highly secure and scalable web applications, including social networks, eCommerce, and online collaboration platforms. - Source: dev.to / over 2 years ago
Give https://cakephp.org/ a try. It also is one of the oldest ones out there, so quite mature and stable while being rather lightweight. Serving JSON API seems like a good fit. Source: over 3 years ago
You can download it and review the documentation here: https://cakephp.org/. - Source: dev.to / over 3 years ago
As the name of the service says it will work best with Laravel but it is not a problem to modify code from other frameworks to make it work the same way. I have several applications created this way in CakePHP. I have this set to manual after clicking the deploy button, but if you want you can turn on quick deploy and then it will publish the application after a push to the main branch (or another one, depending... - Source: dev.to / over 3 years ago
Setup time matters too. The delta between Runpod and bare-metal providers like Lambda Labs is large. Reaching an equivalent setup on a bare VM requires provisioning the instance, configuring the OS and CUDA drivers, installing Docker, setting up your orchestration layer (Kubernetes or Slurm), deploying your inference container, configuring autoscaling rules, and wiring up your load balancer. Thatโs a realistic... - Source: dev.to / 5 months ago
Let's do the math for a representative setup: GPT-OSS-120B via Together.ai ($0.15/$0.60) vs self-hosting on H100s from Lambda Labs at $2.99/hr ($2,183/mo). A single H100 running a 70B model produces roughly 50 tokens/second on average, which works out to about 130M tokens per month. - Source: dev.to / 6 months ago
How does this compare to https://lambdalabs.com/. - Source: Hacker News / about 3 years ago
Another option is to pay for AWS server with a beefy GPU and enough RAM. It's not too cheap, but isn't expensive either if you aren't planning to run it 24/7. Or get a GPU cluster from a company that offers stuff for ML specifically, it might be easier to set up compared to AWS and in some cases cheaper. Like, for example, lambdalabs that offers H100 gpu for 2 bucks per hour. Source: about 3 years ago
I used some of the cloud GPUs on Vast.ai, but I also tried Lambda Labs, and these days I have my own docker container setup which can be deployed to a VM on Google Cloud and used more programatically. Source: over 3 years ago
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