Instructions to use busetolunay/block with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use busetolunay/block 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("busetolunay/block") prompt = "[trigger] style, isometric view of a collapsed scarecrow, its stick frame broken and lying in the dirt, straw spilling out of torn fabric, with its hat lying a few feet away, detailed textures on the frayed fabric and dry straw, surrounded by an overgrown patch of the farm field" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
block_lora_2
Model trained with AI Toolkit by Ostris

- Prompt
- [trigger] style, isometric view of a collapsed scarecrow, its stick frame broken and lying in the dirt, straw spilling out of torn fabric, with its hat lying a few feet away, detailed textures on the frayed fabric and dry straw, surrounded by an overgrown patch of the farm field
Trigger words
You should use bl0ck 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 busetolunay/block
Base model
black-forest-labs/FLUX.1-dev