Instructions to use hiddenbox/pore_dream4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hiddenbox/pore_dream4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/realistic-vision-v51", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("hiddenbox/pore_dream4") prompt = "a photo of pore dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- a6771432320949dbc9257954aefa619cbeaec9ffbd609804ce7fce89f3f1368f
- Size of remote file:
- 6.53 MB
- SHA256:
- 847dc5e7794e254c2808c196e8317fcddcc0b76bf1d1cfe954ca8ccd343cf9a3
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