Instructions to use blanchon/dc_flux_krea_diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use blanchon/dc_flux_krea_diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("blanchon/dc_flux_krea_diffusers", 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
Update pipeline.py
Browse files- pipeline.py +1 -1
pipeline.py
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@@ -42,7 +42,7 @@ from diffusers.utils import (
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from diffusers.utils.torch_utils import randn_tensor
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from diffusers.pipelines.pipeline_utils import DiffusionPipeline
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from diffusers.pipelines.flux.pipeline_output import FluxPipelineOutput
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from fluxdcgen_transformer import DCFluxTransformer2DModel
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if is_torch_xla_available():
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import torch_xla.core.xla_model as xm
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from diffusers.utils.torch_utils import randn_tensor
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from diffusers.pipelines.pipeline_utils import DiffusionPipeline
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from diffusers.pipelines.flux.pipeline_output import FluxPipelineOutput
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from .fluxdcgen_transformer import DCFluxTransformer2DModel
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if is_torch_xla_available():
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import torch_xla.core.xla_model as xm
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