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General Knowledge Fine-Tuning Dataset

Broad general knowledge and trivia

Fine-tune a model on this dataset

$19 for the dataset. Training is priced separately by model, starting at $47.

What is in this dataset

807 instruction-response pairs covering broad general knowledge and trivia. Each pair is a realistic question with a full written answer, in the JSONL format used for supervised fine-tuning. No synthetic filler, no duplicated rows.

Example pairs

Real rows from the dataset, shown in full.

What is the capital of Mongolia, and can you tell me something interesting about its history?

The capital of Mongolia is Ulaanbaatar, which translates to 'Red Hero.' It was founded in 1639 as a nomadic Buddhist monastery center and has since become the country’s political, economic, and cultural hub. Notably, it is the coldest capital city in the world, with average winter temperatures often dropping below -20°C (-4°F).

Why is the signing of the Magna Carta in 1215 considered a pivotal moment in history?

The Magna Carta, signed by King John of England at Runnymede, is pivotal because it established the principle that everyone, including the monarch, is subject to the law. It introduced concepts like due process and trial by jury, and its clauses influenced later documents such as the U.S. Constitution and the Universal Declaration of Human Rights, laying groundwork for constitutional governance.

Can you explain how photosynthesis works in simple terms?

Photosynthesis is the process by which plants convert sunlight into energy. Using chlorophyll in their leaves, plants absorb carbon dioxide from the air and water from the soil. With sunlight as an energy source, they transform these into glucose (a sugar for food) and oxygen, which is released as a byproduct. The overall chemical equation is: 6CO₂ + 6H₂O + light → C₆H₁₂O₆ + 6O₂.

Who this is for

Broad-knowledge assistants and trivia products.

Which models this works with

The dataset is plain JSONL, so it works with any instruction-tuned open model. On Rebiha you can train it directly on:

Training uses LoRA, or QLoRA on a 4-bit base for larger models. Your base model's weights are never modified — training produces a separate adapter.

How it works

  1. Pick this dataset and a base model.
  2. Rebiha runs the job on a managed GPU. You set up nothing.
  3. Download your model: a ready-to-run GGUF, plus developer assets (adapter, tokenizer, configs).

Fine-tuning or RAG?

Use RAG when the model needs facts that change — your prices, your documents, today's inventory. Use fine-tuning when you want consistent style and structure without prompting for it every time. This dataset teaches the shape of a good answer in this domain, not facts to look up.

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