import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("IsraelBenDavid/orientation-control-lora-only-x")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]control-lora-IsraelBenDavid/orientation-control-lora-only-x
These are Control LoRA weights trained on black-forest-labs/FLUX.1-dev with new type of conditioning. You can find some example images below.
prompt: A soccer ball with a solid background
prompt: A soccer ball with a solid background
prompt: A soccer ball with a solid background
prompt: A soccer ball with a solid background
prompt: A credit card with a solid background
prompt: A remote control with a solid background
prompt: A bed with a solid background
prompt: A car with a solid background
License
Please adhere to the licensing terms as described here
Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
Training details
[TODO: describe the data used to train the model]
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Model tree for IsraelBenDavid/orientation-control-lora-only-x
Base model
black-forest-labs/FLUX.1-dev