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- GitHub - mlfoundations datacomp: DataComp: In search of the next . . .
DataComp is a competition about designing datasets for pre-training CLIP models Instead of iterating on model design and hyperparameter tuning like in traditional benchmarks, in DataComp your task is to curate a multimodal pre-training dataset with image-text pairs that yields high accuracy on downstream tasks
- DataComp：探索下一代多模态数据集 - CSDN博客
本文介绍了用于语言模型的数据对比测试平台（DataComp for Language Models, DCLM），旨在通过受控数据集实验改进语言模型。DCLM提供了一个标准化的语料库，包含从Common Crawl提取的240万亿个词元，基于OpenLM框架的有效预训练方案，以及53个下游评估任务的广泛套件。
- DataComp: In search of the next generation of multimodal datasets
To address this shortcoming in the ML ecosystem, we introduce DataComp, a testbed for dataset experiments centered around a new candidate pool of 12 8 billion image-text pairs from Common Crawl
- Datacomp | Appraisals, Inspections Manufactured Housing Market Data
Datacomp is the nation’s largest, independent provider of manufactured and mobile home valuations, inspections and market data We make your decision process safer, simpler and more cost-effective by ensuring you receive the most timely, accurate information available
- DataComp
Welcome to DataComp, the machine learning benchmark where the models are fixed and the challenge is to find the best possible data! Prior competitions in machine learning have focused on finding the best model, with a fixed set of training and test data
- DataComp：寻找下一代多模态数据集 - 智源社区 - baai. ac. cn
DataComp: In search of the next generation of multimodal datasets 解决问题： 这篇论文旨在解决机器学习领域中数据集受到的研究关注不足的问题，提出了一个名为DataComp的基准测试，旨在通过固定训练代码，让研究者通过提出新的训练集来创新，从而推动多模态数据集的发展。
- 【LLM Pretrain data】DCLM - 知乎 - 知乎专栏
我们引入了用于语言模型的DataComp (DCLM)，这是一个用于受控数据集实验的测试平台，旨在提升语言模型的性能。 作为DCLM的一部分， 我们提供了从Common Crawl中提取的240T tokens的标准化语料库，基于 OpenLM 框架的有效预训练方案，以及一个包含53项下游评估的广泛
- DataComp Documentation — DataComp 0. 0. 7-dev documentation
DataComp is an open source Python package for domain independent multimodal longitudinal dataset comparisons It serves as an investigative toolbox to assess differences between multiple datasets on feature level
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