Instructions to use mcante/marcio-4p with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mcante/marcio-4p 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("mcante/marcio-4p") prompt = "MARCIO in a chair dressed like a king like in medieval times" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
MARCIO-4p
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- MARCIO in a chair dressed like a king like in medieval times
Trigger words
You should use MARCIO to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, Forge, etc.
Weights for this model are available in Safetensors format.
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Model tree for mcante/marcio-4p
Base model
black-forest-labs/FLUX.1-dev