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 tokenizer/tokenizer_config.json from colt12/maxcushion: direct link, hf CLI and curl.
- Browser
- Download file 230 Bytes
-
https://huggingface.co/colt12/maxcushion/resolve/main/tokenizer/tokenizer_config.json
- Command line
-
hf download hf://colt12/maxcushion/tokenizer/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/colt12/maxcushion/resolve/main/tokenizer/tokenizer_config.json
230 Bytes
| { | |
| "model_max_length": 77, | |
| "padding_side": "right", | |
| "truncation_side": "right", | |
| "special_tokens_map_file": null, | |
| "tokenizer_class": "CLIPTokenizer", | |
| "name_or_path": "openai/clip-vit-large-patch14", | |
| "use_fast": false | |
| } |