devActivity
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devActivity is a performance analytics platform that automatically collects data from GitHub, measuring and analyzing developer metrics in real-time. Use devActivity to easily get performance reviews based on contributions activity and use AI-based recommendations for retrospectives. Additionally, devActivity uses badges and other gamified components to motivate developers to write better code.
devActivity
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devActivity's answer
devActivity's answer
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Based on our record, Hugging Face seems to be a lot more popular than devActivity. While we know about 326 links to Hugging Face, we've tracked only 3 mentions of devActivity. 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.
To accurately assess the impact of experiments, you must implement robust tracking and monitoring systems. This involves collecting data on key performance indicators (KPIs), user behavior, and system performance. By carefully analyzing this data, you can identify what's working, what's not, and make informed decisions about whether to continue, modify, or stop your experiments. Tools that provide AI-powered code... - Source: dev.to / 6 months ago
Try devActivity today. With its free plan for up to 7 contributors, you'll be surprised at the data-driven insights that devActivity can provide to help you execute your plans. - Source: dev.to / over 1 year ago
Give devActivity a try! It has a free plan that allows you to manage up to 7 contributors, so there's no risk in exploring how it can empower your team to work smarter and achieve more. - Source: dev.to / over 1 year ago
Hugging Face hosts thousands of open models for NLP, vision, and other tasks. The Inference API (via Inference Providers) lets you call those models over HTTP. The @huggingface/inference package from huggingface.js is the Node.js client. - Source: dev.to / about 2 months ago
Right now, I don't. If model foo is deleted from HuggingFace but its compare rows are still in the DB, those compare pages will still be served at build time. They'll have the old data until the model's row in models.json is removed โ which only happens if the model falls out of the top-500 in the nightly fetch. It's a known gap. For now, the risk is low; popular models don't disappear. A more robust system would... - Source: dev.to / 2 months ago
Apify turned out to be an excellent platform for building multi-agent systems(MAS). It allows seamless integration with modern agentic frameworks like LangGraph, CrewAI, TogetherAI, and Hugging Face. - Source: dev.to / 2 months ago
The garage is not the network. ComfyUI is a workbench. It does not describe how a workflow assembled in it travels to another workbench, what license attaches to the intermediate frames, or who in a multi-tool pipeline counts as the author of the result. Hugging Face is the closest thing the field has to a shared hub for models and datasets, and is a remarkable piece of community infrastructure, and is also a... - Source: dev.to / 2 months ago
All numbers below are reproducible from public APIs and public repository files: citation metadata, GitHub Code Search, the Hugging Face Hub, and root-level packaging files (requirements.txt, pyproject.toml, etc.) in each OSS repo. The org-scoped grep is org: "import albumentations". - Source: dev.to / 3 months ago
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