Downloads · 30 days
33
10% of all-time downloads
AlekseyCalvin/AKHMATOVAflux_fullLora
AKHMATOVAflux_fullLora is a text-to-image model from AlekseyCalvin. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as other.
Downloads · 30 days
33
10% of all-time downloads
All-time downloads
330
Public
Repo size
344 MB
Likes
0
Public
Click a slice to open those files.
.safetensors344 MB · 100%
From the Hugging Face model README
Trained via Ostris' ai-toolkit on 60 vintage photos (most of them colorized by us and/or by Klimbim) capturing the legendary poet Anna Andreevna Akhmatova. For this LoRA we used highly detailed manually-composed paragraph captions. It was trained for 1200 steps at a Transformer Learning Rate of .0005, batch 1, AdamW8bit! Minimal synthetic data (just a few reluctant upscales), zero auto-generated captions! <br>
This is a rank-32 historical LoRA for Flux (whether of a Dev, a Schnell, or a Soon® sort...) <br> Use it to diffusely diversify the presence of Akhmatova's deathless visage in our strange latter-day world! And once you're faced with this poet's iconic penetrating stare, do lend your ears to her as well: listen in to her voice! Wherefrom might this voice resound for you? A dusty paperback? Google search? Maybe a clip on YouTube? Or, say, your very memory reciting verses suddenly recalled?<br> In any case, we'll offer you some echoes to rely on, if you will: Namely, our translations of Akhmatova's verse-works, adapted from a proto-Soviet song-tongue into a Worldish one...<br> And found, along with many other poets' songs and tomes... Over at SilverAgePoets.com!
You should use AKHMATOVA or Anna Akhmatova or vintage autochrome photograph of Anna Akhmatova to summon the poet's latent spirit.
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/AKHMATOVAflux_fullLora', 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