Instructions to use MLbackup/Flux_Scrape_Loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MLbackup/Flux_Scrape_Loras with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MLbackup/Flux_Scrape_Loras", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
metadata
license: mit
language:
- en
base_model:
- black-forest-labs/FLUX.1-Fill-dev
- stabilityai/stable-diffusion-3.5-large
library_name: diffusers
tags:
- graphic
- design
- art
- flux
- sd3.5