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 Settings
- Draw Things
- DiffusionBee
Download config.json from colt12/maxcushion: direct link, hf CLI and curl.
- Browser
- Download file 696 Bytes
-
https://huggingface.co/colt12/maxcushion/resolve/main/config.json
- Command line
-
hf download hf://colt12/maxcushion/config.json
-
curl -L -o config.json https://huggingface.co/colt12/maxcushion/resolve/main/config.json
696 Bytes
| { | |
| "_class_name": "StableDiffusionXLPipeline", | |
| "_diffusers_version": "0.26.0", | |
| "feature_extractor": [ | |
| "feature_extractor", | |
| "CLIPFeatureExtractor" | |
| ], | |
| "safety_checker": [ | |
| "safety_checker", | |
| "StableDiffusionXLSafetyChecker" | |
| ], | |
| "scheduler": [ | |
| "scheduler", | |
| "DPMSolverMultistepScheduler" | |
| ], | |
| "text_encoder": [ | |
| "text_encoder", | |
| "CLIPTextModel" | |
| ], | |
| "text_encoder_2": [ | |
| "text_encoder_2", | |
| "CLIPTextModelWithProjection" | |
| ], | |
| "tokenizer": [ | |
| "tokenizer", | |
| "CLIPTokenizer" | |
| ], | |
| "tokenizer_2": [ | |
| "tokenizer_2", | |
| "CLIPTokenizer" | |
| ], | |
| "unet": [ | |
| "unet", | |
| "UNet2DConditionModel" | |
| ], | |
| "vae": [ | |
| "vae", | |
| "AutoencoderKL" | |
| ] | |
| } |