Instructions to use not-pegasus/IMAGE_MODAL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use not-pegasus/IMAGE_MODAL with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("not-pegasus/IMAGE_MODAL", 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
File size: 787 Bytes
568aa87 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | from __future__ import annotations
from typing import Any
class Timeout(TimeoutError): # noqa: N818
"""Raised when the lock could not be acquired in *timeout* seconds."""
def __init__(self, lock_file: str) -> None:
super().__init__()
self._lock_file = lock_file
def __reduce__(self) -> str | tuple[Any, ...]:
return self.__class__, (self._lock_file,) # Properly pickle the exception
def __str__(self) -> str:
return f"The file lock '{self._lock_file}' could not be acquired."
def __repr__(self) -> str:
return f"{self.__class__.__name__}({self.lock_file!r})"
@property
def lock_file(self) -> str:
""":return: The path of the file lock."""
return self._lock_file
__all__ = [
"Timeout",
]
|