In contrast, our current options for evaluating applications built using LLMs are far more limited. Here, I see two major types of applications. For applications designed to deliverunambiguous, right-or-wrong responses, we have reasonable options. Let’s say we want an LLM to read a resume a...
【Awesome-LLM-Eval:一份精选的工具、演示、论文和文档清单,用于评估类似ChatGPT、LLaMA和GLM这样的大型语言模型】'Awesome-LLM-Eval - Awesome-LLM-Eval: a curated list of tools, demos, papers, docs for Evaluation on Large Language Models like ChatGPT, LLaMA, GLM' JUN GitHub: github.com/onejune2018...
工具选择。为了识别实践者常用的开源测试工具,论文在Github上搜索了“llm evaluation”,并根据GitHub星数对结果进行排名,这表明了实践者的兴趣和使用情况。论文仅考虑专注于测试和评估的仓库,排除了模型库、运行基准测试的工具以及其他没有突出测试包的LLM仓库。论文还限制了分析范围,仅限于适用于各种LLM部署(如总结、问...
awsragmlopsllmllmopsgenaifine-tuning-llmllm-evaluationml-system-design UpdatedDec 23, 2024 Python The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM Observability all in one place. prompt-engineeringprompt-managementllm-toolsllm-frameworkllm-playgroundllm-plat...
Humanloop is an enterprise-grade AI evaluation platform with best-in-class prompt management and LLM observability.
吴恩达《深入探讨使用权重和偏差进行 LLM 评估|Deep Dive into LLM Evaluation with Weights & Biases》中英字 59:12 吴恩达《LLM Agent Fine-Tuning: Enhancing Task Automation with Weights & Biases》中英字幕 01:00:56 吴恩达《FastAPI for Machine Learning: Live coding an ML web application》中英字幕 01...
Evaluation consists of prompting an LLM to predict the correct sequence of tools after every user utterance in a conversation. Thus, evaluating on a single conversation requires an LLM to correctly predict multiple sub-tasks. Predictions are compared against the ground truth to determine success for...
evaluation data is vital for model providers. Furthermore, these data and metrics must be collected to comply with upcoming regulations.ISO 42001, theBiden Administration Executive Order, andEU AI Actdevelop standards, tools, and tests to help ensure that AI systems are ...
4. 评估(Evaluation) 评估对于下一轮专家组的构成调整和提升起到至关重要的作用,使用奖励反馈机制评估当前状态与期望目标之间的差距,并给出口头反馈,解释为什么当前状态仍然不令人满意并提供建设性建议,讨论下一轮如何改进。 其中奖励反馈机制可以由人工定义(人机协作循环),也可以由自动反馈模型定义,具体取决于实现方式...
评估(Evaluation) 评估对于下一轮专家组的构成调整和提升起到至关重要的作用,使用奖励反馈机制评估当前状态与期望目标之间的差距,并给出口头反馈,解释为什么当前状态仍然不令人满意并提供建设性建议,讨论下一轮如何改进。 其中奖励反馈机制可以由人工定义(人机协作循环),也可以由自动反馈模型定义,具体取决于实现方式。