Instructions to use bep40/Malloca2024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bep40/Malloca2024 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("bep40/Malloca2024") prompt = "Malloca" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: Malloca
output:
url: images/1000023338.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Malloca
license: apache-2.0
Malloca 2024

- Prompt
- Malloca
Model description
Malloca
Trigger words
You should use Malloca to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.