Instructions to use hiddenbox/dogs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hiddenbox/dogs 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/dogs") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-1000/optimizer.bin from hiddenbox/dogs: direct link, hf CLI and curl.
- Browser
- Download file 6.53 MB
-
https://huggingface.co/hiddenbox/dogs/resolve/main/checkpoint-1000/optimizer.bin
- Command line
-
hf download hf://hiddenbox/dogs/checkpoint-1000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/hiddenbox/dogs/resolve/main/checkpoint-1000/optimizer.bin
6.53 MB
- Xet hash:
- 5210dc1780f21c7228b90b398b778eed91d3e477122adba6aa86f73d0a1465cd
- Size of remote file:
- 6.53 MB
- SHA256:
- 5b92905b9e85e883429a080e962e7fb7db1cff4e7b5d8bc5ac6d4b3c606fff5d
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