ROSA LUXEMBURG FLUXenburg Low-Rank Adapter (LoRA) V.2
The great revolutionary rises from under sea! Meet face-to-face a reincorporealized and (within your own spirit) resurrected visionary pioneer & hero of the classless future, and a martyr for the its cause, now becoming revitalized everyplace!
Click over to YouTube via this exclusive link to watch LIVING UNDER C.: our little musical film starring many versions of Rosa Luxenburg, and of others besides. The film includes several songs, much archival footage and imagery re-interpreted by trained models, synthetic singing, real minimally processed singing, quotes from political theory and from poetry, and much else!
It seems this LoRA, trained on the Colossus 2.1 Dedistilled Flux trained+merged model by AfroMan4Peace, available here in a diffusers format and here at CivitAI, could be used fairly well with any version of FLUX. Inference on Schnell-based models seems to work better with this adapter than with any identity-transferring LoRA's we've tried that were trained on a distilled Flux Dev.
Trigger words
You should use ROSA Fluxenburg
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/Rosa_FLUXenburg_LoRA_v2_Dedistilled-Trained_SilverAgeLiberators', 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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