Instructions to use hiddenbox/pore_dream5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hiddenbox/pore_dream5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SG161222/Realistic_Vision_V5.1_noVAE", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("hiddenbox/pore_dream5") prompt = "a photo of a1sfv dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 50f6c943f90e80db1340dcc68cf6056beb91715e38c99defff5319421c2d9ed1
- Size of remote file:
- 6.53 MB
- SHA256:
- ba05ba5cc9715ec8368e218507832c43eed5e81813d1c0dc312e1c465d81106f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.