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 Any | |
| from datetime import datetime | |
| from sqlalchemy import MetaData | |
| from sqlalchemy.orm import DeclarativeBase | |
| NAMING_CONVENTION = { | |
| "ix": "ix_%(table_name)s_%(column_0_N_name)s", | |
| "uq": "uq_%(table_name)s_%(column_0_N_name)s", | |
| "ck": "ck_%(table_name)s_%(constraint_name)s", | |
| "fk": "fk_%(table_name)s_%(column_0_name)s_%(referred_table_name)s", | |
| "pk": "pk_%(table_name)s", | |
| } | |
| class Base(DeclarativeBase): | |
| metadata = MetaData(naming_convention=NAMING_CONVENTION) | |
| def to_dict(obj: Any, include_none: bool = False) -> dict[str, Any]: | |
| fields = obj.__table__.columns.keys() | |
| out: dict[str, Any] = {} | |
| for field in fields: | |
| val = getattr(obj, field) | |
| if val is None and not include_none: | |
| continue | |
| if isinstance(val, datetime): | |
| out[field] = val.isoformat() | |
| else: | |
| out[field] = val | |
| return out | |
| # TODO: Define models here | |