I'm really struggling with processing large texts, especially lengthy articles or technical guides. I find that the main ideas often get buried under lots of repetitive content, making it hard to grasp the key takeaways. For instance, instead of saying, "Set up a local DNS-server like Pi-hole and configure it for your entire network," I'd prefer something concise like, "Set up a local DNS-server (e.g. Pi-hole) for whole LAN". It's pretty much half the length but still conveys the same meaning.
I have an idea for a browser extension that could tackle this problem, ideally working offline and being open-source. The plan is to create an algorithm that captures web page text, summarizes it, and displays it in a clean, distraction-free manner. However, I'm on the lookout for guidance on key concepts, tools for prototyping this algorithm, and any libraries that could help with text simplification. If you have any insights or similar projects in mind, I'd love to hear about them!
1 Answer
You might want to check out Ollama, which lets you play around with various models on your PC. Just tinker with prompts to find the right output format. But honestly, local models can be quite underwhelming compared to online versions. They often need way more resources than an average computer can provide to avoid inaccuracies. So, while experimenting is cool, keep in mind that many still prefer to pay for online models because they tend to perform better.
Yeah, exactly! Local models can be tricky. It sometimes feels like more hassle than it’s worth, especially when you have to double-check everything.