Instructions to use Squiddy3/AlanShatter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Squiddy3/AlanShatter 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("Squiddy3/AlanShatter") prompt = "Alan Shatter" 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("Squiddy3/AlanShatter")
prompt = "Alan Shatter"
image = pipe(prompt).images[0]Flux

- Prompt
- Alan Shatter
Model description
Alan Shatter
Trigger words
You should use Alan Shatter 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 Squiddy3/AlanShatter
Base model
black-forest-labs/FLUX.1-dev