Trained via Ostris'
ai-toolkit on 50 high-resolution scans of 1910s/1920s posters & artworks by the great Soviet
poet, artist, & Marxist activist Vladimir Mayakovsky.
For this training experiment, we first spent many days rigorously translating the textual elements (slogans, captions, titles, inset poems, speech fragments, etc), with form/signification/rhymes intact, throughout every image subsequently used for training.
These translated textographic elements were, furthermore, re-placed by us into their original visual contexts, using fonts matched up to the sources.
We then manually composed highly detailed paragraph-long captions, wherein we detailed both the graphic and the textual content of each piece, its layout, as well as the most intuitive/intended apprehension of each composition.
This repo contains the 2400 step checkpoint and samples. Training went for 5000 steps at a DiT Learning Rate of .00001, batch 1, with the adafactor optimizer, and the text encoders trained alongside the DiT!
No synthetic data was used for the training, nor any auto-generated captions! Everything was manually and attentively pre-curated with a deep respect for the sources used.
Check out our
translations of Mayakovsky's verse-works, adapted from a proto-Soviet song-tongue into a Worldish one...
And found, along with many other poets' songs and tomes...
Over
at SilverAgePoets.com!
For more details, including weighting, merging and fusing LoRAs, check the
documentation on loading LoRAs in diffusers