: Use benchmarks like InfiniteBench , which tests model performance on contexts exceeding 100k tokens .
Depending on your research focus (web scraping, social media analysis, or manufacturing), you can download the following 100K-scale datasets: Download 100K mixed txt
: Use the 100K scale to train models using pre-processing techniques like tokenization, stemming, and lemmatization for identifying misinformation in mixed-source data. Direct Sources for .txt Data : Use benchmarks like InfiniteBench , which tests
: A classic recommendation system dataset containing 100,000 ratings. Researchers often use this to test collaborative filtering and hybrid recommendation algorithms. Researchers often use this to test collaborative filtering
: A large-scale dataset for LLM-based web information extraction. It combines multilingual markdown/text content from real web pages with natural-language prompts and validated JSON responses.
: This dataset includes over 100,000 textual descriptions of real-life choice dilemmas sourced from social media and surveys, ideal for computational analysis of trade-offs and behavioral themes.
