Open-LLM Leaderboard 2.0-New Benchmarks from HuggingFace скачать в хорошем качестве

Open-LLM Leaderboard 2.0-New Benchmarks from HuggingFace

Learn about the Open LLM Leaderboard 2.0 by HuggingFace! Check out new benchmarks, top models, and the implications for the AI community. 🌟 ⭐️What You'll Learn: The importance of a standardized LLM leaderboard 🏆 Challenges in comparing different language models 🤔 New benchmarks introduced: MMLU Pro, GPQA, MUSR, MATH, IFEval, and BBH 📚 Examples of new benchmark questions and tests 🧩 Implementation and ranking of models using new benchmarks 📈 Implications for major providers and the AI community 🌐 Top models on the Open LLM Leaderboard 🌟 ⛓️Connect with Us: 👍 Like | 🔗 Share | 📢 Subscribe | 💬 Comments + Questions LinkedIn:   / casedonebyai   YouTube:    / @casedonebyai   Facebook:   / casedonebyai   TikTok:   / casedonebyai   Github: https://www.github.com/casedone SubStack: https://casedonebyai.substack.com 🎬Quick navigation: 00:30 Importance of the Leaderboard 01:11 Problems in LLM Comparison: Lack of Transparency and Reproducibility, Saturation Problem in Benchmarks, Leakage of Benchmarks into Training Data, Errors in Benchmarks 04:21 Motivation for Upgrading Open LLM Leaderboard 04:39 Introduction of New Evaluation Methods 04:47 Popular Benchmarks: MMLU Pro Version, GPQA (Google Proof Q&A Benchmark), MUSR (Multi-Step Soft Reasoning Test), Math (Mathematics Attitude Test of Heuristics), IF Evaluation (Instruction Following), BBH (Big Bench Hard) 09:02 Benchmark Samples Introduction 15:30 Implementation of New Benchmarks in Open LLM Leaderboard 17:39 LMSyS Chatbot Arena and Future Adoption #AI #LLM #Leaderboard #MachineLearning #Benchmarking #TechNews ArtificialIntelligence #HuntingFest