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
base_model: black-forest-labs/FLUX.1-dev
pipeline_tag: text-to-image
instance_prompt: Birdcage
widget:
  - text: neon Maserati Birdcage driving at sunset
    output:
      url: >-
        https://generated-images.weights.gg/cm4xapxa410s8gh17dqkv86xk/lora_image_1.webp

Maserati Birdcage Flux LoRA

Trained on Weights.gg.

Used 15 pictures of the Maserati Birdcage 75th Concept.

Trigger words

You should use Birdcage 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('fazemasta/birdcage', 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