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-10100/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-10100/optimizer.bin
- Command line
-
hf download hf://hiddenbox/pore_dream/checkpoint-10100/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/hiddenbox/pore_dream/resolve/main/checkpoint-10100/optimizer.bin
6.53 MB
- Xet hash:
- 359ee35583be92c4243c88bd8d1ac3b3eec01519c046ec2b1c915e7fbc408dd0
- Size of remote file:
- 6.53 MB
- SHA256:
- 3071635c576f5e7cb7bd316658dd908bef7f11447be4a29335c25dde9d16dcac
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