Instructions to use ampp/Maleko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ampp/Maleko 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("ampp/Maleko") prompt = "Maleko dressed as a king, wearing a Samoan garment with palm trees in the background" 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("ampp/Maleko")
prompt = "Maleko dressed as a king, wearing a Samoan garment with palm trees in the background"
image = pipe(prompt).images[0]Maleko

- Prompt
- Maleko dressed as a king, wearing a Samoan garment with palm trees in the background
Trigger words
You should use Maleko 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 ampp/Maleko
Base model
black-forest-labs/FLUX.1-dev