Instructions to use mhnakif/comfy2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mhnakif/comfy2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mhnakif/comfy2", 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 typing import TypeVar | |
| class SingletonMetaclass(type): | |
| T = TypeVar("T", bound="SingletonMetaclass") | |
| _instances = {} | |
| def __call__(cls, *args, **kwargs): | |
| if cls not in cls._instances: | |
| cls._instances[cls] = super(SingletonMetaclass, cls).__call__( | |
| *args, **kwargs | |
| ) | |
| return cls._instances[cls] | |
| def inject_instance(cls: type[T], instance: T) -> None: | |
| assert cls not in SingletonMetaclass._instances, ( | |
| "Cannot inject instance after first instantiation" | |
| ) | |
| SingletonMetaclass._instances[cls] = instance | |
| def get_instance(cls: type[T], *args, **kwargs) -> T: | |
| """ | |
| Gets the singleton instance of the class, creating it if it doesn't exist. | |
| """ | |
| if cls not in SingletonMetaclass._instances: | |
| SingletonMetaclass._instances[cls] = super( | |
| SingletonMetaclass, cls | |
| ).__call__(*args, **kwargs) | |
| return cls._instances[cls] | |
| class ProxiedSingleton(object, metaclass=SingletonMetaclass): | |
| def __init__(self): | |
| super().__init__() | |