Instructions to use CalvinHerbst/EditorialZine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CalvinHerbst/EditorialZine 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("CalvinHerbst/EditorialZine") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- 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("CalvinHerbst/EditorialZine")
prompt = "-"
image = pipe(prompt).images[0]Editorial Zine

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Model description
Strength 1.0 - 1.8
Use tag "N$CFW" in your prompt. Optional tags include: editorial, text, booklet, spiral bound, typography, magazine, collage, hand made, fashion
Trigger words
You should use N$CFW to trigger the image generation.
You should use editorial to trigger the image generation.
You should use text to trigger the image generation.
You should use booklet to trigger the image generation.
You should use spiral bound to trigger the image generation.
You should use typography to trigger the image generation.
You should use magazine collage to trigger the image generation.
You should use hand made to trigger the image generation.
You should use fashion 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 CalvinHerbst/EditorialZine
Base model
black-forest-labs/FLUX.1-dev