Instructions to use akrao9/Boomer-T2I with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use akrao9/Boomer-T2I with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("akrao9/Boomer-T2I", 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
- Draw Things
- DiffusionBee
Update pipeline_boomer.py
Browse files- pipeline_boomer.py +1 -1
pipeline_boomer.py
CHANGED
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@@ -239,7 +239,7 @@ class BoomerPipeline(DiffusionPipeline):
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prompt: Union[str, List[str]],
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steps: int = 32,
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seed: int | None = None,
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-
cfg_scale: float = 4.
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cfg_rescale: float = 0.5,
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substeps: int = 5,
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offload_text_encoder: bool = True,
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prompt: Union[str, List[str]],
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steps: int = 32,
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seed: int | None = None,
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+
cfg_scale: float = 4.0,
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cfg_rescale: float = 0.5,
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substeps: int = 5,
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offload_text_encoder: bool = True,
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