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Found 3 papers, 1 papers with code
Connecting Large Language Model Agent to High Performance Computing Resource
The Large Language Model agent workflow enables the LLM to invoke tool functions to increase the performance on specific scientific domain questions.
LSHBloom: Memory-efficient, Extreme-scale Document Deduplication
Deduplication is a major focus for assembling and curating training datasets for large language models (LLM) -- detecting and eliminating additional instances of the same content -- in large collections of technical documents.
WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data
Together with the pipeline, we will additionally release 9. 5M urls to word documents which can be processed using WordScape to create a dataset of over 40M pages.
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