Training With Differential Privacy:然后作者就没仔细说怎么train了。 Curating the Training Data:第一步:去除训练语料中隐私相关的信息(identifying and filtering personal information or content with restrictive terms of use)。第二步:de-duplicate the data去重训练数据来减少隐私信息出现的重复次数。第三步:选用...
Data Quality是之前被LLaMa-2提起并引起大家重视,Meta也发了一篇论文说明在instruction tuning这个阶段Quality(质量)比Quantity(数量)更重要,Lima: Less is more for alignment. [6]。 Lima显现了,只要1,000条instruction tuning data,就可以比很多训练更久的LLMs表现更好。 这个结论我相信很多相关领域从业者都知道,...
falcon的refinedWeb paper(arxiv.org/pdf/2306.0111)是一篇把基于爬虫爬取数据的处理讲的这么详细的paper之一,后续我会再精读The Pile , C4 等其他数据集,总结出更多的爬虫爬取的网页数据的pre-training data处理方法。 在对LLM dataset调研的过程中,我发现中文的NLP大型语料真的很少,除开没有common crawl这样大型...
< Panda LLM: Training Data and Evaluation for Open-Sourced Chinese Instruction-Following Large Language Models搜索 阅读原文 下载APP
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首先,进入到data目录: cddata 找到目录下的compress_data.py, 在该文件中修改需要压缩的数据路径: SHARD_SIZE =10# 单个文件存放样本的数量, 示例中使用很小,真实训练可以酌情增大...defbatch_compress_preatrain_data():""" 批量压缩预训练数据。
Data curation is the first, and arguably the most important, step in the pretraining and continuous training of large language models (LLMs) and small language models (SLMs). NVIDIA recently announced the open-source release of NVIDIA NeMo Curator, a data curation framework that prepares large...
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Data Preparation on Spark Before we start fine tuning the model, we need to extract the numeric features from the text, which are used as inputs to the model. ForHugging Facemodels this is facilitated by theTransformerslibrary using itsTokenizerclass. ...
Data Organization 整个预训练数据收集完毕后,如何组织成为结构化的预训练数据供给模型训练是现阶段很多科研机构研究的方向。 5.如何通过数据的依赖关系组织预训练数据可以最大限度地让模型学习到存储在预训练数据的知识,这是现阶段大家最关注的方向。其中构造更长依赖的文本数据似乎是现阶段的一个突破口,更长的文本依赖...