Instructions to use Javisantacata/picasso with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Javisantacata/picasso 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("Javisantacata/picasso") prompt = "Generame un cuadro abstracto retrato de un hombre colorido" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
picasso
Model description
Lora del artista Pablo Picasso
Trigger words
You should use Generame un cuadro abstracto retrato de un hombre colorido to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Training at fal.ai
Training was done using fal.ai/models/fal-ai/flux-lora-fast-training.
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Model tree for Javisantacata/picasso
Base model
black-forest-labs/FLUX.1-dev