Instructions to use FredZhang7/paint-journey-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FredZhang7/paint-journey-v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FredZhang7/paint-journey-v1", 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
Commit ·
d9d0497
1
Parent(s): f0c7de4
Update unet/config.json
Browse files- unet/config.json +2 -3
unet/config.json
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@@ -1,7 +1,6 @@
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{
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"_class_name": "UNet2DConditionModel",
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"_diffusers_version": "0.
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"_name_or_path": "paint_journey",
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"act_fn": "silu",
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"attention_head_dim": 8,
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"block_out_channels": [
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],
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"upcast_attention": false,
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"use_linear_projection": false
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}
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{
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"_class_name": "UNet2DConditionModel",
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"_diffusers_version": "0.10.2",
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"act_fn": "silu",
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"attention_head_dim": 8,
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"block_out_channels": [
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],
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"upcast_attention": false,
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"use_linear_projection": false
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}
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