Alexander_BLOK_Flux_LoRA_SilverAgePoets_v2_face_only

Alexander Blok Flux Low-Rank Adapter (LoRA) for SilverAgePoets.com

An adapter to reproduce the likeness of the legendary Symbolist/Modernist Russian and Soviet poet: <br> Alexander Blok (b.1880-d.1921) <br>

CLICK HERE TO READ OUR TRANSLATION OF BLOK'S "STRANGER"/"NEZNAKOMKA"

This version of our Blok LoRA was the product of an experimental training to transfer face/attribute-features from historical photos with minimal compute time by using a high rank training, just short of a full model fine-tune, and a relatively high learning rate, but with a minimal number of steps. <br> This is the version from rank256 (if we recall correctly) and 250 steps. <br>

As you can see, even 250 steps was far too many, as the resulting adapter lacks generalizability, and tries to make any prompt into a circa-21st century professional photo portrait. <br>

On the flipside, it has arguably learned Blok's face (in his later life) somewhat better than our other versions. <br>

Therefore, we've decided to still post it here. <br>

Ideally, we ought to extract only the learned features into a much smaller-sized LoRA file. <br> As that would really shrink the file size and possibly aid with generalizability as well. <br> We will get around to doing that eventually. <br> For now, anyone interested in using this locally, please forgive for us the huge file size! <br>

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Trigger words

You should use BLOK_02.CR2 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/Alexander_BLOK_Flux_LoRA_SilverAgePoets_v2_face_only', 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