Instructions to use jimipatel/Mrwhite3000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jimipatel/Mrwhite3000 with Diffusers:
pip install -U diffusers transformers accelerate
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("jimipatel/Mrwhite3000") prompt = "m4r7wh7t3" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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("jimipatel/Mrwhite3000")
prompt = "m4r7wh7t3"
image = pipe(prompt).images[0]Mrwhite3000

- Prompt
- m4r7wh7t3
Trigger words
You should use m4r7wh7t3 to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
- Downloads last month
- 1
Model tree for jimipatel/Mrwhite3000
Base model
black-forest-labs/FLUX.1-dev