Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use digiplay/PersonaStyleCheckpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use digiplay/PersonaStyleCheckpoint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("digiplay/PersonaStyleCheckpoint", 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
Download text_encoder/pytorch_model.bin from digiplay/PersonaStyleCheckpoint: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/digiplay/PersonaStyleCheckpoint/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://digiplay/PersonaStyleCheckpoint/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/digiplay/PersonaStyleCheckpoint/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- f0c22eb53d2b1404587c7751505d2cc843346098b4f433f294d12c4e7dfef444
- Size of remote file:
- 492 MB
- SHA256:
- 005e914f509974d797fa58990ae4ee72ef99ab168c854833a73fdddfda034398
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