AlekseyCalvin/Rosa_FLUXenburg_LoRA_v2_Dedistilled-Trained_SilverAgeLiberators

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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! <br>

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.

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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