Instructions to use imagepipeline/Logo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use imagepipeline/Logo 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("imagepipeline/Logo") prompt = "anime, graphic novel style, girl with pink pigtails wearing a blue vand white frock eating an ice-cream" 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("imagepipeline/Logo")
prompt = "anime, graphic novel style, girl with pink pigtails wearing a blue vand white frock eating an ice-cream"
image = pipe(prompt).images[0] A newer version of this model is available: black-forest-labs/FLUX.1-dev
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Model tree for imagepipeline/Logo
Base model
black-forest-labs/FLUX.1-dev