Search Results for "tune"
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Showing 3 open source projects for "tune"
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Cloud tools for web scraping and data extractionAutomate web data collection with cloud tools that handle anti-bot measures, browser rendering, and data transformation out of the box. Extract content from any website, push to vector databases for RAG workflows, or pipe directly into your apps via API. Schedule runs, set up webhooks, and connect to your existing stack. Free tier available, then scale as you need to.
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kerl
Easy building and installing of Erlang/OTP instances
Easy building and installing of Erlang/OTP instances. Kerl aims to be shell agnostic and its only dependencies, excluding what's required to actually build Erlang/OTP, are curl and git. All is done so that, once a specific release has been built, creating a new installation is as fast as possible. We are supporting the current OTP release version and 2 prior release versions (same as upstream OTP.) Older OTP releases may or may not work. We will advance release support as new releases of OTP... -
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Lando
A development tool for all your projects that is fast, easy, powerful
...Use your favorite IDE. See CLI tools working out-of-the-box. Distribute working dev environments to your whole team. Junior devs get a rocket boost while senior devs can tune settings to make their best astro racer. The local development and DevOps tool trusted by professional developers across the galaxy. Free yourself from the mind-forged manacles of lesser dev tools. Save time, headaches, frustration and do more real work. Quickly specify and painlessly spin up the services and tooling needed to develop all their projects. -
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Gin Config
Gin provides a lightweight configuration framework for Python
...Users can define default parameter values, scoped configurations, and modular references to functions, classes, or instances, resulting in highly composable and dynamic experiment setups. Gin is particularly popular in TensorFlow and PyTorch projects, where researchers and developers need to tune numerous interdependent parameters across models, datasets, optimizers, and training pipelines.
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