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Lambda Face Recognition API
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GitLab
Lambda Face Recognition APIGitLab is well-suited for developers, DevOps engineers, project managers, and teams that require robust CI/CD capabilities, strong security features, and an open-source platform that can be self-hosted or used as a cloud service. It is particularly beneficial for organizations looking for a comprehensive solution to streamline their development workflows.
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Based on our record, GitLab should be more popular than Lambda Face Recognition API. It has been mentiond 144 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.
We use GitHub here as an example, but there are also other hosts you could explore like GitLab and BitBucket. - Source: dev.to / 3 months ago
Expertise. The SaaS provider is declaring: "I am good at XYZ; I can deliver it better than any of my competitors, and I constantly work to improve how I deliver it." Who do you think can better run GitLab, your already overworked Operations team, or GitLab itself? - Source: dev.to / 5 months ago
Integration Capabilities: How easily does it plug into your daily workflow? Look for deep integrations with your IDE, source control (like GitHub or GitLab), and especially your CI/CD pipeline. - Source: dev.to / 6 months ago
Connect your GitLab account for seamless version control. - Source: dev.to / 8 months ago
Web Check CI stands out because it is the first CI/CD module of its kind available for GitLab! It's built on Google's Baseline initiative, the new standard for web platform compatibility. Instead of guessing which features are safe to use, developers get authoritative answers based on real browser support data. - Source: dev.to / 10 months 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
GitHub - Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.
Mattermost - Mattermost is an open source alternative to Slack.
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
Vast.ai - GPU Sharing Economy: One simple interface to find the best cloud GPU rentals.
CircleCI - CircleCI gives web developers powerful Continuous Integration and Deployment with easy setup and maintenance.
ipinfo.io - Simple IP address information.