Instructions to use hf-internal-testing/tiny-sdxl-custom-all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-sdxl-custom-all with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-sdxl-custom-all", 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 unet/my_unet_model.py (#4)
Browse files- Update unet/my_unet_model.py (c1f4a0eac1247843fb3ea601a2dd43f588fa467f)
- unet/my_unet_model.py +1 -1
unet/my_unet_model.py
CHANGED
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@@ -42,7 +42,7 @@ from diffusers.models.embeddings import (
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Timesteps,
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)
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from diffusers.models.modeling_utils import ModelMixin
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-
from diffusers.models.unet_2d_blocks import (
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UNetMidBlock2DCrossAttn,
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UNetMidBlock2DSimpleCrossAttn,
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get_down_block,
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Timesteps,
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)
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from diffusers.models.modeling_utils import ModelMixin
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+
from diffusers.models.unets.unet_2d_blocks import (
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UNetMidBlock2DCrossAttn,
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UNetMidBlock2DSimpleCrossAttn,
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get_down_block,
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