Datasetpublic

rodriguescarson/adaption-astro-insights-qa-aug

Astrology Insights Q&A (Invented) (Augmented) Questions about world religious traditions and related topics with explanatory answers. Rows 999 Domain astrology Format data.parquet, one row per example Licence other Built for supervised fine-tuning (SFT) experiments on Adaption AutoScientist Columns Column Description original_prompt The prompt (user turn) as uploaded. original_completion The target response as uploaded.… See the full description on the dataset page: https://huggingface.co/datasets/rodriguescarson/adaption-astro-insights-qa-aug.

sourceHugging Faceotherupdated 3h agoView on Hugging Face

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Dataset Card

Astrology Insights Q&A (Invented) (Augmented)

Questions about world religious traditions and related topics with explanatory answers.


Rows	999
Domain	astrology
Format	`data.parquet`, one row per example
Licence	other
Built for	supervised fine-tuning (SFT) experiments on Adaption AutoScientist

Columns

Column	Description
`original_prompt`	The prompt (user turn) as uploaded.
`original_completion`	The target response as uploaded.
`enhanced_prompt`	Prompt after Adaption processing (rewrite or augmentation).
`enhanced_completion`	Response after Adaption processing (rewrite or augmentation).

How it was built

Generated with Adaption's Invent feature (the combined variant merges several of these).

Sources and licence

—Generated with Adaption Invent.

Notes

—This dataset was expanded by Adaption's augmentation, which adds platform-generated rows alongside the seed. The added rows are general-purpose and do not all match the dataset's topic; Adaption does not publish their provenance, so the licence is listed as other. The export does not mark which rows are seed and which were added.
—Rows were generated by a language model through Adaption Invent and have not been fact-checked row by row.

Loading

python

from datasets import load_dataset
ds = load_dataset("rodriguescarson/adaption-astro-insights-qa-aug", split="train")

python

import pandas as pd
df = pd.read_parquet("hf://datasets/rodriguescarson/adaption-astro-insights-qa-aug/data.parquet")

Published by Carson Rodrigues (Hugging Face, Kaggle).