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: PCCLFGRTV
library_name: diffusers
inference:
  parameters:
    width: 1024
    height: 1024
widget:
  - text: PCCLFGRTV style. Superman feeding a cow
    example_title: Superman with a cow
    output:
      url: samples/superman-cow.png
  - text: >-
      This is a Cubist-style painting that employs geometric shapes, muted
      colors, and overlapping forms to depict a still life scene. PCCLFGRTV
      style. Night scene. a raining Gotham city. Batman is facing the camera.
    example_title: Batman in Gotham city
    output:
      url: samples/batman-gotham-city.png
  - text: PCCLFGRTV style. Spiderman in a rural scene.
    example_title: Spiderman
    output:
      url: samples/spiderman.png

Flux Lora Piccoli Figurative

Trained on Replicate using:

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

Trigger words

You should use PCCLFGRTV 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('lichorosario/flux-lora-piccoli', 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