README.md

metadata

license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
language:
  - en
tags:
  - flux
  - diffusers
  - lora
  - replicate
base_model: black-forest-labs/FLUX.1-dev
pipeline_tag: text-to-image
instance_prompt: BLOK_02.CR2
widget:
  - text: >-
      BLOK_02.CR2, 1905, full height, a best quality color photo portrait
      of       Alexander Blok writing a poem in 1905, curly hair, Edwardian coat
    output:
      url: images/example_y2ucjfyiz.png
  - text: >-
      young BLOK_02.CR2 in Petersburg, 1905, full height, a best quality color
      photo portrait of Alexander Blok strolling in St Petersburg in 1905 while
      writing a poem in 1905, curly hair, Edwardian coat
    output:
      url: images/example_pat2lbcsh.png
  - text: >-
      Generated example for model
      AlekseyCalvin/Alexander_BLOK_Flux_LoRA_SilverAgePoets_v3. Prompt: young
      BLOK_02.CR2 in Petersburg, 1905, full height, a best quality color photo
      portrait of Alexander Blok strolling in St Petersburg in 1905 while
      writing a poem in 1905, curly hair, Edwardian coat
    output:
      url: images/example_bvut2tyo4.png

Alexander Blok FLUX Adapter Version 3 (aka "2_1")

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/BlokFlux2_1', 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