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@@ -12,9 +12,15 @@ datasets:
 # Dancing Chibi Figures — baseline checkpoints
 
 Reference checkpoints for the [sprited/dancing-chibi-figures](https://huggingface.co/datasets/sprited/dancing-chibi-figures)
-dataset, trained with the pure-PyTorch trainer in the [dataset's GitHub repo](https://github.com/sprited-ai/dancing-chibi-figures)
+dataset, trained with the **pure-PyTorch** trainer in the [dataset's GitHub repo](https://github.com/sprited-ai/dancing-chibi-figures)
 (`train/video_ddpm.py` — factorised 3D UNet, v-prediction, cosine schedule, EMA).
 
+**Why this repo exists:** the dataset ships two learning tracks. The diffusers track (links at the bottom) teaches the
+standard tooling everyone uses; this track is the ~600-line from-scratch version where you can read every line of the
+model, the schedule and the sampler — and it is where the **video** models live (diffusers has no tiny video pipeline).
+These checkpoints are the "fully-trained" reference the [Colab tutorial](https://github.com/sprited-ai/dancing-chibi-figures/blob/main/notebooks/dancing_chibi_figures_colab.ipynb)
+compares your short training runs against.
+
 | file | what | steps |
 |---|---|---|
 | `unet_img64.pt` | unconditional 64px image model (`--frames 1`) | 30k |