Crawl4LLM
An efficient web crawler tool for LLM pre-training, focusing on efficiently crawling high-quality web page data.
Product Details
Crawl4LLM is an open source web crawler project that aims to provide efficient data crawling solutions for the pre-training of large language models (LLM). It helps researchers and developers obtain high-quality training corpus by intelligently selecting and crawling web page data. The tool supports multiple document scoring methods and can flexibly adjust crawling strategies according to configuration to meet different pre-training needs. The project is developed based on Python, has good scalability and ease of use, and is suitable for use in academic research and industrial applications.
Main Features
How to Use
Target Users
This product is mainly aimed at researchers and developers who need to efficiently crawl web page data for LLM pre-training. It is suitable for users who want to obtain high-quality training corpus with limited resources, especially professionals in the fields of natural language processing and artificial intelligence.
Examples
Researchers used Crawl4LLM to crawl high-quality documents from the ClueWeb22 dataset for pre-training of LLM.
Developers can use Crawl4LLM's flexible configuration to customize crawling strategies to meet the pre-training needs of specific projects.
The team efficiently crawled data through Crawl4LLM and combined it with the DCLM framework for model evaluation and optimization.
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