Instructions to use Aybeeceedee/knollingcase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Aybeeceedee/knollingcase with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Aybeeceedee/knollingcase", dtype=torch.bfloat16, device_map="cuda") 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 text_encoder/pytorch_model.bin from Aybeeceedee/knollingcase: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/Aybeeceedee/knollingcase/resolve/refs%2Fpr%2F1/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Aybeeceedee/knollingcase@refs/pr/1/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Aybeeceedee/knollingcase/resolve/refs%2Fpr%2F1/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- eb7b4d2adbecfd41d23424c00c0ba7a60a6c31855f459ceb0a2e625183c84eaf
- Size of remote file:
- 492 MB
- SHA256:
- 1ab8eba125da6eec4ad0a4bdf221dbf9a5912a8154438fd446588d79ad89b0f1
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