In this tutorial, we will guide you through building an advanced financial data reporting tool on Google Colab by combining multiple Python libraries. You’ll learn how to scrape live financial data from web pages, retrieve historical stock data using yfinance, and visualize trends with matplotlib. Also, the tutorial demonstrates how to integrate an interactive UI… →
Pre-trained LLMs require instruction tuning to align with human preferences. Still, the vast data collection and rapid model iteration often lead to oversaturation, making efficient data selection a crucial yet underexplored area. Existing quality-driven selection methods, such as LIMA and AlpaGasus, tend to overlook the importance of data diversity and complexity, essential for enhancing model… →
Optimizing large-scale language models demands advanced training techniques that reduce computational costs while maintaining high performance. Optimization algorithms are crucial in determining training efficiency, particularly in large models with extensive parameter counts. While optimizers like AdamW have been widely adopted, they often require meticulous hyperparameter tuning and high computational resources. Finding a more efficient alternative… →
CONCLUSION: The administration of pronase prior to gastroscopy enhances visual field clarity, reduces examination time, and increases the detection rates of precancerous lesions and early cancer. →
CONCLUSION: OSA can effectively control patients’ postoperative pain with lower perioperative haemodynamic variability. It also has lower perioperative haemodynamic variability and acute pain in patients with high pain sensitivity, making it suitable for laparoscopic cholecystectomy. →
Oral-drug based regimens are useful in certain circumstances for transplant-ineligible newly diagnosed multiple myeloma (TI-NDMM), but few studies have compared Ixazomib based regimen with lenalidomide based regimen head-to-head. We carried out a prospective randomized, open, parallel group trial in patients with TI-NDMM in 3 China centers from March 2020 to December 2022. Sixty-three patients were… →
Large-scale reinforcement learning (RL) training of language models on reasoning tasks has become a promising technique for mastering complex problem-solving skills. Currently, methods like OpenAI’s o1 and DeepSeek’s R1-Zero, have demonstrated remarkable training time scaling phenomenon. Both models’ benchmark performance and response length consistently and steadily increase without any sign of saturation as the training… →