Instructions to use bbbboiwow/cocccck with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bbbboiwow/cocccck with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("bbbboiwow/cocccck", 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
| import math, cv2, random, torch, torchvision | |
| import numpy as np | |
| import nodes, folder_paths # 기본노드, 파일로드 | |
| class abyz22_path_generator: | |
| def __init__(self): | |
| pass | |
| def INPUT_TYPES(s): | |
| return { | |
| "required": { | |
| "basic_path": ("STRING", {"default": ""}), | |
| "start_num": ("INT", {"default": 1, "min": 1, "max": 3000}), | |
| }, | |
| } | |
| RETURN_TYPES = ("STRING",) | |
| RETURN_NAMES = ("Text",) | |
| FUNCTION = "run" | |
| CATEGORY = "abyz22" | |
| def run(self, *args, **kwargs): | |
| basic_path, start_num = kwargs["basic_path"], kwargs["start_num"] | |
| t = basic_path + str(start_num) | |
| return (t,) | |