Instructions to use hiddenbox/pore_dream with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hiddenbox/pore_dream with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("hiddenbox/pore_dream") prompt = "a photo of pore" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-100/optimizer.bin from hiddenbox/pore_dream: direct link, hf CLI and curl.
- Browser
- Download file 6.53 MB
-
https://huggingface.co/hiddenbox/pore_dream/resolve/main/checkpoint-100/optimizer.bin
- Command line
-
hf download hf://hiddenbox/pore_dream/checkpoint-100/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/hiddenbox/pore_dream/resolve/main/checkpoint-100/optimizer.bin
6.53 MB
- Xet hash:
- 77e4c042619f4d35a34f1507264f171e7e540182f4d58da628873c298273a73b
- Size of remote file:
- 6.53 MB
- SHA256:
- b20b6f82165e8ee0e792a0d167f95367834e1d3e22276759105788c8ffc793b3
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