Instructions to use hiddenbox/poodle_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hiddenbox/poodle_3 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/poodle_3") 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-2500/pytorch_model.bin from hiddenbox/poodle_3: direct link, hf CLI and curl.
- Browser
- Download file 3.28 MB
-
https://huggingface.co/hiddenbox/poodle_3/resolve/main/checkpoint-2500/pytorch_model.bin
- Command line
-
hf download hf://hiddenbox/poodle_3/checkpoint-2500/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hiddenbox/poodle_3/resolve/main/checkpoint-2500/pytorch_model.bin
3.28 MB
- Xet hash:
- f1a2cf35e84141dfca329a9ec895c16f1217a8a75c3ec0711bef809bf9cad915
- Size of remote file:
- 3.28 MB
- SHA256:
- a60501a850d6f5d97ee4589f5105ed2333490a6c01caf85bea3576524945a557
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