Instructions to use Boogu/Boogu-Image-0.1-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Boogu/Boogu-Image-0.1-Base with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Boogu/Boogu-Image-0.1-Base", 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
File size: 1,168 Bytes
a1c0f0f | 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 | # Copyright (C) 2026 Boogu Team.
# This repository is a fork by Boogu Team; modifications have been made.
"""
Compatibility entry point for the released Boogu base pipeline scheduler.
The inference code in this repository owns the canonical scheduler
implementation. Keeping another full copy here easily causes drift between the
released pipeline package and the active codebase. Diffusers only needs this
module to expose `FlowMatchEulerDiscreteScheduler` for `model_index.json`, so
this file intentionally re-exports the repository class.
"""
try:
from boogu.schedulers.scheduling_flow_match_euler_discrete_time_shifting import (
FlowMatchEulerDiscreteScheduler,
FlowMatchEulerDiscreteSchedulerOutput,
)
except ModuleNotFoundError as exc:
if exc.name != "boogu":
raise
raise ModuleNotFoundError(
"Failed to import the canonical Boogu scheduler implementation. "
"Run inference from the Boogu-Image repository root "
"or add that directory to PYTHONPATH before loading the pipeline."
) from exc
__all__ = [
"FlowMatchEulerDiscreteScheduler",
"FlowMatchEulerDiscreteSchedulerOutput",
]
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