LLMs Course Github 👉 https://github.com/peremartra/Large-Language-Model-Notebooks-Course/tree/main/3-LangChain Introduction to LangChain and Agents: Building Intelligent Applications Curiosit...

If you want to 𝗹𝗲𝗮𝗿𝗻 in a 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝘄𝗮𝘆 to 𝗯𝘂𝗶𝗹𝗱 𝗟𝗟𝗠 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 using good 𝗟𝗟𝗠𝗢𝗽𝘀 principles… We want to announce that we just 𝗿𝗲𝗹𝗲𝗮𝘀𝗲𝗱 𝟴 𝗠𝗲𝗱𝗶𝘂𝗺 𝗹𝗲𝘀𝘀𝗼𝗻𝘀 for the 𝗛𝗮𝗻𝗱𝘀-𝗼𝗻 𝗟𝗟𝗠𝘀 𝗰𝗼𝘂𝗿𝘀𝗲 that will put ...

LLM2Vec: Transform LLMs into Embedding Models Curiosity: Can we transform decoder-only LLMs into powerful text encoders? What happens when we enable bidirectional attention and contrastive learnin...

Introducing Llama 3.1 Yesterday’s Llama 3.1 release marked a big milestone for LLM researchers and practitioners. Llama 3.1 405B is the biggest and most capable LLM with openly available LLMs. A...

Data analyst agent: get your data’s insights in the blink of an eye ✨ Curiosity: What insights can we retrieve from this? How does this connect to innovation in the field? Curiosity: In this note...

Autonomous agents are designed to achieve specific objectives through self-guided instructions. With the emergence and growth of large language models (LLMs), there is a growing trend in utilizi...

UDP (User Datagram Protocol) is used in various software architectures for its simplicity, speed, and low overhead compared to other protocols like TCP. 🔹𝗟𝗶𝘃𝗲 𝗩𝗶𝗱𝗲𝗼 𝗦𝘁𝗿𝗲𝗮𝗺𝗶𝗻𝗴 Many VoIP and video...

👉 Read our announcement blog post: https://huggingface.co/blog/llama31 🤗 Model card for the 405B on the Hub: https://huggingface.co/meta-llama/Meta-Llama-3.1-405B-FP8 Meta’s Llam...

Visualize Your RAG Data: EDA for Retrieval-Augmented Generation Curiosity: How can we visualize RAG embedding data to understand retrieval quality? What insights can interactive visualizations rev...

A Survey of Prompt Engineering Methods in Large Language Models Curiosity: What are the most effective prompt engineering techniques? How can we systematically understand and apply prompt engineer...