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End of preview. Expand in Data Studio
CatDataset1k
Dataset of 1000 images of cats (domestic cats, Felis catus) for training models,
experiments and fine-tuning (image generation, classification, etc.).
- Query:
cat - Caption / label for every image:
cat - Files:
cat_0000.jpg...cat_0999.jpg(JPEG) - Sources: Wikimedia Commons + Flickr (via Openverse), open licenses
How to download / use
1. Load directly with the datasets library (recommended)
from datasets import load_dataset
ds = load_dataset("debugdll/DataCat1k")
# ds["train"][0]["image"] -> PIL image
# ds["train"][0]["text"] -> "cat"
No token required — the dataset is public. Total size ~ a few hundred MB.
Streaming (no full download, images loaded on demand):
ds = load_dataset("debugdll/DataCat1k", streaming=True)
row = next(iter(ds["train"]))
2. Download the files with the CLI
pip install huggingface_hub
huggingface-cli download debugdll/DataCat1k
3. Download with git
git clone https://huggingface.co/datasets/debugdll/DataCat1k
4. Download individual images (browser / direct link)
https://huggingface.co/datasets/debugdll/DataCat1k/resolve/main/cat_0000.jpg
Change the filename cat_0000.jpg in the link to get any other image.
Format
metadata.csv— columnsfile_name,text- The CSV + images use the standard Hugging Face
imagefolderlayout, soload_dataset("debugdll/DataCat1k")is inferred automatically.
Training usage (diffusers LoRA / text-to-image)
from datasets import load_dataset
ds = load_dataset("debugdll/DataCat1k", split="train") # column: image, text="cat"
Notes
- Caption for every image:
cat - All images are public-domain / openly licensed photos
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