When you're trying to get the best performance out of Python, most developers immediately jump to complex algorithmic fixes, using C extensions, or obsessively running profiling tools. However, one of ...
This project provides an end-to-end pipeline for fine-tuning large language models using LiteLLM. It handles every step of the fine-tuning process—from preparing and validating training data, to ...
Why use this? The Cypress monorepo contains 30+ packages managed with Yarn workspaces, Lerna, Nx, Gulp, Vite, Webpack, and GraphQL codegen. Setting up a local development environment requires ...
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