Nov 27, 2024 · In this post, we present a generative AI-powered semantic search solution that empowers business users to quickly and accurately find relevant data assets across various enterprise data sources.

Feb 28, 2024 · Abstract: This paper embarks on an exploration into the Large Language Model (LLM) datasets, which play a crucial role in the remarkable advancements of LLMs. The datasets serve as the foundational infrastructure analogous to a root system that sustains and nurtures the development of LLMs.

Data is the most valuable asset in LLM development. When building a dataset, we target the three following characteristics: Accuracy: Samples should be factually correct and relevant to their corresponding instructions. This can involve using solvers for math and unit tests for code.

1 day ago · It categorizes LLM applications and explores how users' occupations relate to the types of applications they use. By integrating real-world data, REALM offers insights into LLM adoption across different domains, providing a foundation for future research on their evolving societal roles. A dedicated dashboard this https URL presents the data.

Training a chatbot LLM that can follow human instruction effectively requires access to high-quality datasets that cover a range of conversation domains and styles. In this repository, we provide a curated collection of datasets specifically designed for chatbot training, including links, size, language, usage, and a brief description of each ...

Oct 28, 2024 · Large language models (LLMs) are fueled by vast amounts of text data, ranging from books and code to articles and web crawl information. This data equips LLMs with the statistical knowledge to understand human language patterns. Here, we'll discuss some popular datasets for training LLMs for text generation tasks.

We in-troduce three typical LLM based data management applications, including database optimization (e.g., system diagnosis), data pro-cessing (e.g., data standardization), and data...

6 days ago · The automated generation of design RTL based on large language model (LLM) and natural language instructions has demonstrated great potential in agile circuit design. However, the lack of datasets and benchmarks in the public domain prevents the development and fair evaluation of LLM solutions. This paper highlights our latest advances in open datasets and benchmarks from three perspectives ...

The demand for high-quality datasets is rapidly increasing across sectors such as healthcare, finance, and cybersecurity, yet challenges like data scarcity and privacy concerns persist. To address this, we introduce a framework for synthetic data generation that empowers users to create realistic datasets while maintaining privacy. The framework leverages fine-tuned Large Language Models (LLMs ...

Data preparation is the first and a very important step towards any Large Language Model (LLM) development. This paper introduces an easy-to-use, extensible, and scale-flexible open-source data preparation toolkit called Data Prep Kit (DPK). DPK is architected and designed to enable users to scale their data preparation to their needs. With DPK they can prepare data on …