Instructions to use Ngene787/Faice_unconditional_diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ngene787/Faice_unconditional_diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Ngene787/Faice_unconditional_diffusion", 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
Upload folder using huggingface_hub
Browse files- model_index.json +2 -2
- unet/config.json +2 -2
model_index.json
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"DDPMScheduler"
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],
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"unet": [
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"
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"
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]
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}
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"DDPMScheduler"
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],
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"unet": [
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"diffusers",
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"UNet2DModel"
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]
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}
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unet/config.json
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{
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"_class_name": "
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"_diffusers_version": "0.32.2",
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"act_fn": "silu",
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"add_attention": true,
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"UpBlock2D"
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],
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"upsample_type": "resnet"
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}
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{
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"_class_name": "UNet2DModel",
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"_diffusers_version": "0.32.2",
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"act_fn": "silu",
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"add_attention": true,
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"UpBlock2D"
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],
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"upsample_type": "resnet"
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}
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