Via Ostris' ai-toolkit on 50 high-resolution scans of 1910s/1920s posters & artworks by the great Soviet poet, artist, & Marxist activist Vladimir Mayakovsky.
Prior to 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.
For the given first version of the training, unlike Version 2 (linked below), we used auto-captions, and did not train the text encoder.
This first not-very-successful version of the resultent LoRA (check out V.2 here) was trained on regular old FLUX.1-Dev.
On this run, the training went for mere 1500 steps at a DiT Learning Rate of .0004, batch 3, with the Adamw8bit optimizer!
No synthetic data was used

This is a rank-32/alpha-32 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 Constructivist art to trigger the image generation.

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/MayakArt', 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