---
license: apache-2.0
language:
- en
tags:
- flux
- diffusers
- lora
- replicate
- image-generation
- flux-diffusers
- diffusers
- photo
- realism
- character
- historical person
- poetry
- literature
- history
- archival
base_model: "AlekseyCalvin/Colossus_2.1_dedistilled_by_AfroMan4peace"
pipeline_tag: text-to-image
library_name: diffusers
emoji: 🔜

instance_prompt: Anna AKHMATOVA, blemished skin texture with slight wrinkles 

widget:
- text: >-
    agitprop Constructivist poster of the poet Anna AKHMATOVA calling out "JOIN RCA!" in a speech bubble, over satirical cartoon of cool punky diverse teenage gen-z revolutionaries
  output:
    url: AkhmDedistilled1.jpg
- text: >-
    vintage side-view photograph of young Anna AKHMATOVA, classic analog color photography
  output:
    url: AnnaPoeticsWill.jpg

---
<Gallery />

# Anna Akhmatova Flux Low-Rank Adapter (LoRA) Version 2 by SilverAgePoets.com
Trained on a dataset of 60 vintage photos (most of them colorized by us and/or by [Klimbim](https://klimbim2020.wordpress.com/)). <br>  
And capturing the legendary **poet**: <br> 
**Anna Andreevna Akhmatova** <br> *(b.06/26/1889-d.03/05/1966)* <br> 

For this LoRA we used highly detailed manually-composed paragraph captions. <br>  
It was trained for 1600 steps (a 1300 checkpoint also added) at a Diffusion-Transformer Learning Rate of .0004, dim/alpha of 32, batch 1, AdamW8bit optimizer! Minimal synthetic data (just a few reluctant upscales), zero auto-generated captions! <br> 

**VERSION 3 NOTE:** <br> 

This third version of the Akhmatova LoRA was trained on the **Colossus 2.1 Dedistilled Flux model by AfroMan4Peace**, available [here](https://huggingface.co/AlekseyCalvin/Colossus_2.1_dedistilled_by_AfroMan4peace) in a diffusers format and [here at CivitAI](https://civitai.com/models/833086/colossus-project-flux). <br>  
As of writing this blurb, we haven't yet tested this LoRA enough to say much concretely, but our other adapters trained over de-distilled modifications of FLUX have been shown to be more versatile than most base-model trained LoRAs in regards to compatibility and output variability. <br> 

In parallel, we've also trained yet another Akhmatova LoRA (version 2) over a regular version of Flux, to enable a better basis for comparative testing. That version is available in a different repo [here](https://huggingface.co/AlekseyCalvin/Akhmatova_Flux_LoRA_SilverAgePoets_v2_regularFluxD). <br> 

**MORE INFO:** <br> 

This is a **rank-32 historical LoRA for Flux** (whether of a [Dev](https://huggingface.co/black-forest-labs/FLUX.1-dev), a [Schnell](https://huggingface.co/black-forest-labs/FLUX.1-schnell), or a [Soon®](https://huggingface.co/AlekseyCalvin/HistoricColorSoonr_Schnell) 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](https://www.silveragepoets.com/akhmatovamain)!**

## Trigger words
You should use `AKHMATOVA` or `Anna Akhmatova` or `vintage autochrome photograph of Anna Akhmatova` to summon the poet's latent spirit.

## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)

```py
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/Akhmatova_Flux_LoRA_SilverAgePoets_v2_regularFluxD', 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](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)