Search Results for "data entry"

OpenDAN is an open-source Personal AI OS , that consolidates various AI modules in one place for your personal use. The goal of OpenDAN (Open and Do Anything Now with AI) is to create a Personal AI OS , which provides a runtime environment for various Al modules as well as protocols for interoperability between them. With OpenDAN, users can securely collaborate with various AI modules using their private data to create powerful personal AI agents, such as butlers, lawyers, doctors, teachers,...

Introducing MPT-7B, the first entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B. MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k. Large language models (LLMs) are changing the world, but for those outside well-resourced industry labs, it can be extremely difficult to train and deploy...

...The project aims to solve the challenge of discovering high-quality datasets by collecting resources that are otherwise scattered across multiple research communities and repositories. Each dataset entry typically includes information such as size, language coverage, intended use cases, and links to the original data sources. The repository focuses particularly on datasets useful for chatbot training, instruction-following tasks, and alignment training scenarios. By organizing these resources into a curated hub, the project helps researchers and developers identify the most relevant training corpora for building conversational AI systems. ...