Instructions to use aztro/mabama-flux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aztro/mabama-flux 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("aztro/mabama-flux") prompt = "photo of mabama a beautiful woman" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- 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("aztro/mabama-flux")
prompt = "photo of mabama a beautiful woman"
image = pipe(prompt).images[0]mabama-flux

- Prompt
- photo of mabama a beautiful woman
- Negative Prompt
- Low quality
Model description
Modelo FLux
Trigger words
You should use mabama to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for aztro/mabama-flux
Base model
black-forest-labs/FLUX.1-dev