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-1000/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-1000/optimizer.bin
- Command line
-
hf download hf://hiddenbox/pore_dream5/checkpoint-1000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/hiddenbox/pore_dream5/resolve/main/checkpoint-1000/optimizer.bin
6.53 MB
- Xet hash:
- b9e142560f1ab495ca0a3fe700f77039a2a51a53752c9c6eb711a61950af80c5
- Size of remote file:
- 6.53 MB
- SHA256:
- 23a17bfd035ecfdc400a95defd6a79b140b101f675b63b31c8a996ef6c9efa84
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.