Mayakovsky Style Soviet Constructivist Posters & Cartoons Flux LoRA – Version 2 – by SOON®
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 version of the resultent LoRA was trained on our custom Schnell-based checkpoint (Historic Color 2), available here in fp8 Safetensors and here in Diffusers format.
To produce this earlier checkpoint (the full 5000 run is available in another repo), the training went on for 3600 steps at a DiT Learning Rate of .00002, batch 1, with the ademamix8bit optimizer, and both 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.
This is a rank-32/alpha-64 Constructivist Art & Soviet Satirical Cartoon LoRA for Flux (whether of a Dev, a Schnell, or a Soon® sort...)
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!
Trigger words
You should use MAYAK style
or MAYAK style Constructivist poster art
or MAYAK style satyrical drawing
or suchlike to summon the poet's deathlessly pens and brushes.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('AlekseyCalvin/Mayakovsky_Posters_2_3600st', weight_name='lora.safetensors')
image = pipeline('your prompt').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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