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 Settings
- Draw Things
- DiffusionBee
Download checkpoint-1200/optimizer.bin from hiddenbox/pore_dream5: direct link, hf CLI and curl.
- Browser
- Download file 6.53 MB
-
https://huggingface.co/hiddenbox/pore_dream5/resolve/main/checkpoint-1200/optimizer.bin
- Command line
-
hf download hf://hiddenbox/pore_dream5/checkpoint-1200/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/hiddenbox/pore_dream5/resolve/main/checkpoint-1200/optimizer.bin
6.53 MB
- Xet hash:
- 5776624a7e632e882245a79ae01d7d55092fe2deabd2e64ae9c28aef7be23bdc
- Size of remote file:
- 6.53 MB
- SHA256:
- 0906c85712e4bac1adad5bb5b20caff494f8a6e2f661ae667ab7fba4969288ce
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.