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: 712 Bytes
bddf20b | 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 32 33 34 35 | # file generated by setuptools-scm
# don't change, don't track in version control
__all__ = [
"__version__",
"__version_tuple__",
"version",
"version_tuple",
"__commit_id__",
"commit_id",
]
TYPE_CHECKING = False
if TYPE_CHECKING:
from typing import Tuple
from typing import Union
VERSION_TUPLE = Tuple[Union[int, str], ...]
COMMIT_ID = Union[str, None]
else:
VERSION_TUPLE = object
COMMIT_ID = object
version: str
__version__: str
__version_tuple__: VERSION_TUPLE
version_tuple: VERSION_TUPLE
commit_id: COMMIT_ID
__commit_id__: COMMIT_ID
__version__ = version = '2025.12.0'
__version_tuple__ = version_tuple = (2025, 12, 0)
__commit_id__ = commit_id = None
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