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("viraj9837/general_prompts")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]control-lora-viraj9837/general_prompts
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: Mark plant placements on a 2D floorplan using colored circles. Use red, blue, and orange in triangular groups of three. Avoid red-blue and orange-blue pairings, straight-line patterns, or sequentially escalating sizes in rows.
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]
- Downloads last month
- 3
Model tree for viraj9837/general_prompts
Base model
black-forest-labs/FLUX.1-dev