From 5af935bd4d424c1ac4397354e657075b9f26337f Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" <41898282+github-actions[bot]@users.noreply.github.com> Date: Wed, 23 Oct 2024 01:58:51 +0000 Subject: [PATCH] awesome-stars category by topic update by github actions cron --- README.md | 11 +++-------- 1 file changed, 3 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index e3c9307..4187ddb 100644 --- a/README.md +++ b/README.md @@ -678,7 +678,6 @@ - [elixir-phoenix](#elixir-phoenix) - [elk](#elk) - [emacs](#emacs) -- [email-campaigns](#email-campaigns) - [email-marketing](#email-marketing) - [embedded-systems](#embedded-systems) - [embeddings](#embeddings) @@ -3261,7 +3260,7 @@ ## benchmark -- [princeton-nlp/SWE-bench](https://github.com/princeton-nlp/SWE-bench) - [ICLR 2024] SWE-Bench: Can Language Models Resolve Real-world Github Issues? +- [princeton-nlp/SWE-bench](https://github.com/princeton-nlp/SWE-bench) - [ICLR 2024] SWE-bench: Can Language Models Resolve Real-world Github Issues? - [benchmark-action/github-action-benchmark](https://github.com/benchmark-action/github-action-benchmark) - GitHub Action for continuous benchmarking to keep performance ## benchmarking @@ -6166,10 +6165,6 @@ - [emacs-vs/codemetrics](https://github.com/emacs-vs/codemetrics) - Plugin shows complexity information - [khoj-ai/khoj](https://github.com/khoj-ai/khoj) - Your AI second brain. Self-hostable. Get answers from the internet or your docs. Use any online or local LLM (e.g gpt, claude, gemini, llama, qwen, mistral). Build custom agents, personalized automati -## email-campaigns - -- [knadh/listmonk](https://github.com/knadh/listmonk) - High performance, self-hosted, newsletter and mailing list manager with a modern dashboard. Single binary app. - ## email-marketing - [knadh/listmonk](https://github.com/knadh/listmonk) - High performance, self-hosted, newsletter and mailing list manager with a modern dashboard. Single binary app. @@ -8708,7 +8703,7 @@ ## language-model -- [princeton-nlp/SWE-bench](https://github.com/princeton-nlp/SWE-bench) - [ICLR 2024] SWE-Bench: Can Language Models Resolve Real-world Github Issues? +- [princeton-nlp/SWE-bench](https://github.com/princeton-nlp/SWE-bench) - [ICLR 2024] SWE-bench: Can Language Models Resolve Real-world Github Issues? - [dair-ai/Prompt-Engineering-Guide](https://github.com/dair-ai/Prompt-Engineering-Guide) - 🐙 Guides, papers, lecture, notebooks and resources for prompt engineering - [arc53/DocsGPT](https://github.com/arc53/DocsGPT) - Chatbot for documentation, that allows you to chat with your data. Privately deployable, provides AI knowledge sharing and integrates knowledge into your AI workflow - [ai-forever/ru-gpts](https://github.com/ai-forever/ru-gpts) - Russian GPT3 models. @@ -13322,7 +13317,7 @@ ## software-engineering -- [princeton-nlp/SWE-bench](https://github.com/princeton-nlp/SWE-bench) - [ICLR 2024] SWE-Bench: Can Language Models Resolve Real-world Github Issues? +- [princeton-nlp/SWE-bench](https://github.com/princeton-nlp/SWE-bench) - [ICLR 2024] SWE-bench: Can Language Models Resolve Real-world Github Issues? - [ByteByteGoHq/system-design-101](https://github.com/ByteByteGoHq/system-design-101) - Explain complex systems using visuals and simple terms. Help you prepare for system design interviews. - [ashishps1/awesome-behavioral-interviews](https://github.com/ashishps1/awesome-behavioral-interviews) - Tips and resources to prepare for Behavioral interviews. - [charlax/professional-programming](https://github.com/charlax/professional-programming) - A collection of learning resources for curious software engineers