Instructions to use hiddenbox/poodle_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hiddenbox/poodle_4 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_4") 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-8000/scheduler.bin from hiddenbox/poodle_4: direct link, hf CLI and curl.
- Browser
- Download file 559 Bytes
-
https://huggingface.co/hiddenbox/poodle_4/resolve/main/checkpoint-8000/scheduler.bin
- Command line
-
hf download hf://hiddenbox/poodle_4/checkpoint-8000/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/hiddenbox/poodle_4/resolve/main/checkpoint-8000/scheduler.bin
559 Bytes
- Xet hash:
- 4dc9a3eeb999ba935253a2fa26810969c053584e385f94704f3a671a0ab34a8f
- Size of remote file:
- 559 Bytes
- SHA256:
- daaa934443c5c291dfe11244e408a9d939504b1132be5006797c7db7fc5c46df
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.