LLMOps.Space
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工具介绍：
LLMOps.Space是一个全球化的LLM从业者和爱好者社区，提供了一个关于LLM部署的内容、讨论和活动的平台。
收录时间：
2023年7月24日
月流量：
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LLMOps.Space 工具信息
什么是LLMOps.Space？
LLMOps.Space是一个全球化的LLM从业者和爱好者社区。它提供了一个平台，用于发布LLM部署相关的内容、讨论和活动。
如何使用 LLMOps.Space？
要使用LLMOps.Space，加入LLMOps Discord服务器并进行自我介绍。浏览网站以获取教育材料、即将举行的讲座和演示、LLM顾问列表、资金新闻、新产品和模块、LLM相关活动以及测试项目列表。
LLMOps.Space 的核心功能
专注于LLM部署的内容和讨论
即将举行的讲座和演示
LLM从业者的教育材料
LLM顾问列表
资金新闻
新产品和模块的新闻
LLM相关活动列表
测试项目列表
LLMOps.Space 的使用案例
#1
寻找教育资源和建立人脉的LLM从业者
#2
对LLM部署进展保持更新兴趣的爱好者
来自 LLMOps.Space 的常见问题
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LLMOps.Space 公司信息
更多关于LLMOps.Space, 请访问 the about us page(https://llmops.space/about-llmopsspace).
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May 2023 - Jan 2025 仅桌面设备
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Advanced RAG: Chunking, Embeddings, and Vector Databases 🚀 | LLMOps
In this talk, Yujian from Zilliz talked about advanced RAG concepts including Chunking, Embeddings, and Vector Databases in RAG (Retrieval Augmented Generation) models Topics that were covered: ✅ Chunking: Understand the concept of chunking and its role in improving the efficiency of information retrieval. Learn how to implement chunking in RAG to optimize the retrieval of relevant information. ✅ Embeddings: Dive into the world of embeddings, a method used to represent text as vectors. Discover how to enhance the performance of RAG models by enabling more accurate and efficient information retrieval. ✅ Vector Databases: Explore the use of vector databases in storing and managing embeddings. Learn how to leverage vector databases to speed up the retrieval process in RAG models. About LLMOps Space - LLMOps.Space is a global community for LLM practitioners. 💡📚 The community focuses on content, discussions, and events around topics related to deploying LLMs into production. 🚀 Join discord: https://llmops.space/discord
Building an LLMOps Stack for Large Language Models | LLMs
In this talk, our speakers Rafael and Puneet from @Databricks talked about the construction and optimization of LLMOps architecture. They discussed various components including MLFlow for Large Language Models (LLMs), Vector Databases, embeddings, and compute optimizations. Topics that are covered: ✅ MLFlow for LLMs: Discover the role of MLFlow in managing and streamlining LLMs. ✅ Vector Databases: Learn about the importance of Vector Databases in the LLMOps stack. Get insights into how they can aid in efficient storage, indexing, and retrieval of high-dimensional vector data. ✅ RAG strategies and techniques ✅ Prompt Tracking & Evaluation: Learn how to evaluate LLMs and the key metrics and methods for evaluating the effectiveness of your large language models. About LLMOps Space - LLMOps.Space is a global community for LLM practitioners. 💡📚 The community focuses on content, discussions, and events around topics related to deploying LLMs into production. 🚀 Join discord: http://llmops.space/discord
The Science of LLM Benchmarks: Methods, Metrics, and Meanings | LLMOps
In this talk, Jonathan discussed LLM benchmarks and their performance evaluation metrics. He addressed intriguing questions such as whether Gemini truly outperformed Open AI GPT-4V. He covered how to review benchmarks effectively and understand popular benchmarks like ARC, HellSwag, MMLU, and more. A step-by-step process to assess these benchmarks critically, helping you understand the strengths and limitations of different models. About LLMOps Space - LLMOps.Space is a global community for LLM practitioners. 💡📚 The community focuses on content, discussions, and events around topics related to deploying LLMs into production. 🚀 Join discord: https://llmops.space/discord
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