TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #15261 · Nov 2
#javascript#123pan#139_cloud#189_cloud#ali_netdisk#aliyun_drive#aria2#baidu#baidu_netdisk#baidunetdisk#baiduyun#motrix#quark_netdisk#tampermonkey#tampermonkey_script#tampermonkey_userscript#tianyi_netdisk#uc_netdisk#userscript#xunlei_netdisk#yidong_netdisk LinkSwift is a browser script that helps you quickly get direct download links for files stored on popular Chinese cloud services like Baidu, Alibaba, 123, and others—saving you time and making downloads easier without needing to visit each service’s website separately. It also improves the look of these cloud storage pages and adds extra features, such as support for different download tools and customizable themes. The main benefit is convenience: you can manage and download your cloud files faster, with a nicer interface, all from your browser. Just install the script using a tool like Tampermonkey, and it works on Chrome, Edge, and other major browsers. https://github.com/hmjz100/LinkSwift
Search: #rlhf
@kejiqu · Post #3986 · 12/21/2025, 08:30 AM
ChatGPT 文风，原产地肯尼亚 肯尼亚作家Marcus Olang指出，其写作风格与ChatGPT高度相似，导致其作品屡被退稿，并引发了关于AI“模仿”人类写作方式的讨论。他认为，AI模型并非原创，而是学习了全球南方，特别是肯尼亚等地区严苛教育体系下形成的规范化写作模式。这一现象与AI模型厂商为降低成本，将RLHF工作外包给非洲国家有关，导致模型在用语习惯上受到影响。此外，研究发现ChatGPT对“delve”等词汇的使用频率异常高，也与非洲RLHF工作者的语言习惯有关。这一现象引发了对AI检测器准确性的质疑，以及对非英语母语者在AI时代可能面临的误判风险的关注。IT之家 🏷#ChatGPT#肯尼亚写作风格#RLHF 📢频道👥群组📝投稿
@yinghexiaozu · Post #1248 · 02/24/2023, 12:00 AM
站在 ChatGPT 的肩膀上 这是 ChatGPT 系列话题之二。我精选了这段时间以来我看到的关于 ChatGPT 的文章、网站和项目。 https://hardcored.substack.com/p/w5 #Newsletter#ChatGPT#AIGC#RLHF#GPT3#HuggingFace
@githubtrending · Post #14655 · 05/01/2025, 01:30 PM
#typescript#electron#llama#llms#lora#mlx#rlhf#transformers Transformer Lab is a free, open-source tool that lets you easily work with large language models on your own computer, offering one-click downloads for popular models like Llama3 and Mistral, fine-tuning across different hardware (including Apple Silicon and GPUs), and features like chatting, training, and evaluating models through a simple interface—saving you from complex setups like CUDA or Python version issues[1][2][5]. https://github.com/transformerlab/transformerlab-app