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Source channel @githubtrending · Post #14845 · Jun 20

#jupyter_notebook#ai#artificial_intelligence#chatgpt#deep_learning#from_scratch#gpt#language_model#large_language_models#llm#machine_learning#python#pytorch#transformer You can learn how to build your own large language model (LLM) like GPT from scratch with clear, step-by-step guidance, including coding, training, and fine-tuning, all explained with examples and diagrams. This approach mirrors how big models like ChatGPT are made but is designed to run on a regular laptop without special hardware. You also get access to code for loading pretrained models and fine-tuning them for tasks like text classification or instruction following. This helps you deeply understand how LLMs work inside and lets you create your own functional AI assistant, gaining practical skills in AI development[1][2][3][4]. https://github.com/rasbt/LLMs-from-scratch

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#jupyter_notebook #ai #artificial_intelligence #chatgpt #deep_learning #from_scratch #gpt #language_model #large_language_models #llm #machine_learning #python #pytorch #transformer

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@githubtrending · Post #15440 · 01/27/2026, 12:00 PM

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#go#config#config_loader#configuration#configuration_file#configuration_management#etcd_client#go#golang#golang_package#s3_bucket#toml#viper#yaml koanf is a lightweight Go library to load config from files (JSON, YAML, TOML), env vars, flags, S3, Vault and more, merging them easily with dot-path keys like "app.server.port". Install core with `go get github.com/knadh/koanf/v2`, add providers/parsers as needed. It's a cleaner Viper alternative with fewer dependencies and better extensibility. This saves you time by simplifying config in apps, letting you override values flexibly without bloat or forced orders. https://github.com/knadh/koanf

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#go #config #config_loader #configuration #configuration_file #configuration_management #etcd_client #golang #golang_package #s3_bucket #toml #viper #yaml