Instructions to use colt12/maxcushion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use colt12/maxcushion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("colt12/maxcushion", 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
- Local Apps
- Draw Things
- DiffusionBee
MaxCushion - SDXL Fine-tuned Model
This is a fine-tuned Stable Diffusion XL (SDXL) model based on FLUX.1-dev. It's designed to generate high-quality images with a focus on [specific theme or style your model specializes in].
Model Details
- Base Model: FLUX.1-dev
- Type: Stable Diffusion XL (SDXL)
- Language(s): English
- License: CreativeML Open RAIL-M
Usage
This model can be used with the diffusers library. Here's a basic example:
from diffusers import StableDiffusionXLPipeline
import torch
model_id = "colt12/maxcushion"
pipe = StableDiffusionXLPipeline.from_pretrained(
model_id, torch_dtype=torch.float16, use_safetensors=True, variant="fp16"
)
pipe = pipe.to("cuda")
prompt = "Your prompt here"
image = pipe(prompt).images[0]
image.save("generated_image.png")
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