该项目利用大型语言模型（LLM）的功能来创建以下内容的简明和信息丰富的摘要：文本：从文章、报告或任何书面内容中提取关键点和主题。演讲：转录和总结口语对话、讲座或播客。
This project leverages the power of Large Language Models (LLMs) to create concise and informative summaries of: Text: Extract key points and themes from articles, reports, or any written content. Speech: Transcribe and summarize spoken conversations, lectures, or podcasts. (2024-02-08, Others, 0KB, 下载0次)
Ask Huberman是一款定制的LLM烧瓶Web应用程序，由RAG（检索增强生成）技术和Chroma的向量数据库提供支持。RAG允许定制LLM行为，而无需昂贵的模型微调成本，在这种情况下，使用Huberman播客的前20集的抄本进行定制。
Ask Huberman is a customized LLM flask webapp powered by RAG (Retrieval Augmented Generation) Technology and a Vector Database from Chroma. RAG allows for customization of LLM behavior without the expensive costs of model finetuning and in this case is customized using transcripts of the first 20 episodes from the Huberman podcast. (2024-02-06, Python, 0KB, 下载0次)
一个巴西机器人，可以播放音乐（带有播放列表！），而您可以与朋友一起玩，并让您在晚上收听播客。在...中...，
A Brazilian bot that plays music (with playlists!) While you play with your friends and let you listen to that podcast in the evening. In addition, I also have memes and games! (2023-09-11, TypeScript, 0KB, 下载0次)
Spotify的播客集群引擎，。。。根据用户的参与度数据创建推荐。参考HBS建议1：“使用NLP分析p...
Introduction and Background Research Spotify Podcast : “Digital audio series - Driving Growth Through Personalization” What is the background project? ? Spotify is known for its personalized playlist feature. ? Spotify relies on machine learning to create recommendations based on users’ engagement data. ? Refer to HBS recommendations1 : “using ... (2022-03-02, HTML, 1080KB, 下载0次)