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: HST
widget:
  - text: >-
      HST style autochrome photo, analog camera, blemished extremely elaborate
      mind-bogglingly fine objects within objects and textures within objects
      within textures within objects within subjects within textures within
      objects within textures within subjects within life within objects within
      textures, film photo,  androgynous communist diverse deities amid peaceful
      revolution within revolt within reform within revolution,  consolidate an
      inset progression of co-extending inspiring psychedelicate psychonautical
      images similar to poetic news cycle coverage,  fearless spirits smitten
      with despairlessness, crisp, detailed timelessness, of future solarpunk
      utopian transurbanities, sublime global disassembly of capitalism,
      postcapitalist society, inspired by Walter Benjamin's Theses on the
      Philosophy of History, photorealistic reportage
    output:
      url: images/example_4k24hxgg7.png

Historic_Color_Dev

Trained on Replicate using:

https://replicate.com/ostris/flux-dev-lora-trainer/train

Trigger words

You should use HST 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/historic_color_dev', 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