Question Extractor: turn text into LLM finetuning data
Generate question/answer training pairs out of raw text. - nestordemeure/question_extractor
Question Extractor: turn text into LLM finetuning data launched on April 20, 2023 with 33 votes, #1,493 of 4,853 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 3 years on.
In plain words
Question Extractor is a tool that converts text into training data suitable for language model finetuning. Available on GitHub, it automates the process of generating question-answer pairs from source material, helping developers and researchers prepare datasets for machine learning projects. The tool is designed for anyone working with LLM training who needs to transform raw text into structured finetuning data efficiently.
written from the facts on this page · September 2026
Does a similar job
all alternatives →
Demystifying Advanced RAG Pipelines2023 · github.com · ▲131I've built an advanced RAG (Retrieval-Augmented Generation) pipeline from scratch to demystify the complex mechanics of modern LLM-powered Question Answering systems. This repository features: -- An implementation of a sub-question query engine from scratch to answer complex user questions. -- Illustrative explanations that unveil the inner workings of the system. -- An analysis of the challenges I faced while working with the system, like prompt engineering and cost estimation. -- Qualitative comparison with similar frameworks like LlamaIndex, offering a broader perspective. Key Takeaway:…


- WSWeb search using a ChatGPT-like model that can cite its sources2022 · beta.sayhello.so · ▲318
We’ve trained a generative AI model to browse the web and answer questions/retrieve code snippets directly. Unlike ChatGPT, it has access to primary sources and is able to cite them when you hover over an answer (click on the text to go to the source being cited). We also show regular Bing results side-by-side with our AI answer. The model is an 11-billion parameter T5-derivative that has been fine-tuned on feedback given on hundreds of thousands of searches done (anonymously) on our platform. Giving the model web access lessens its burden to need to store a snapshot of human knowledge…

Beyond text splitting – improved file parsing for LLMs2024 · github.com · ▲206Improved file parsing for LLM’s. Contribute to Filimoa/open-parse development by creating an account on GitHub.
More ai this month
the category →



Paintings by AI models: programs run through a simulation of oil paint.
AI · 21d ago · stillwet.art
PixVerse R2▲381A real-time world model you can explore and change
AI · 29d ago · world.pixverse.video

Source: Show HN post ↗
Launched alongside, April 2023
the whole month →
- G4
Hi HN, Today we’re launching GPT-4 answers on Phind.com, a developer-focused search engine that uses generative AI to browse the web and answer technical questions, complete with code examples and detailed explanations. Unlike vanilla GPT-4, Phind feeds in relevant websites and technical documentation, reducing the model’s hallucination and keeping it up-to-date. To use it, simply enable the “Expert” toggle before doing a search. GPT-4 is making a night-and-day difference in terms of answer quality. For a question like “How can I RLHF a LLaMa model”, Phind in Expert mode delivers a…
AI · 2023 · phind.com



