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Source channel @githubtrending · Post #14826 · Jun 12

#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data. https://github.com/FareedKhan-dev/all-rag-techniques

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djangoproject

@djangoproject · Post #388 · 07/19/2017, 08:35 PM

https://www.youtube.com/watch?v=D-5V7s0GflU Look mum no hands! From blinking LEDs to a bike speedometer with #MicroPython In this talk I will show you how to use a micro-controller to build a wifi enabled speedometer for your bike, using MicroPython. And some hardware. And a bike (maybe). I will introduce you to the world of MicroPython: a python distribution that runs on micro-controllers. Micro-controllers are small computers that are all around us: in cars, TVs, and your internet connected fridge. We will start with making LEDs blink, then serve webpages, build an interrupt handler and finally put it all together to make a wifi enabled speedometer for a bike.

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djangoproject

@djangoproject · Post #513 · 11/30/2017, 10:00 PM

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