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
| from server import PromptServer | |
| from aiohttp import web | |
| import os | |
| import folder_paths | |
| dir = os.path.abspath(os.path.join(__file__, "../../user")) | |
| if not os.path.exists(dir): | |
| os.mkdir(dir) | |
| file = os.path.join(dir, "autocomplete.txt") | |
| async def get_autocomplete(request): | |
| if os.path.isfile(file): | |
| return web.FileResponse(file) | |
| return web.Response(status=404) | |
| async def update_autocomplete(request): | |
| with open(file, "w", encoding="utf-8") as f: | |
| f.write(await request.text()) | |
| return web.Response(status=200) | |
| async def get_loras(request): | |
| loras = folder_paths.get_filename_list("loras") | |
| return web.json_response(list(map(lambda a: os.path.splitext(a)[0], loras))) | |