Text-to-Image
Diffusers
StableDiffusionPipeline
stable-diffusion
sygil-diffusion
sygil-devs
finetune
stable-diffusion-1.5
Instructions to use Sygil/Sygil-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Sygil/Sygil-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("Sygil/Sygil-Diffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "environment art, realistic" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Commit ·
aeb499b
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Parent(s): 0c18eeb
Upload 2 files
Browse files- text_encoder/config.json +1 -1
text_encoder/config.json
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{
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"_name_or_path": "
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"architectures": [
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"CLIPTextModel"
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],
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{
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"_name_or_path": "D:\\Alejandro\\Projects\\Python\\AI\\ImageGen\\Automatic1111\\models\\dreambooth\\sygil-diffusion-v0.4\\working\\text_encoder",
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"architectures": [
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"CLIPTextModel"
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],
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