Instructions to use orinteractive/silly_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use orinteractive/silly_test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("orinteractive/silly_test") prompt = "MYFACE" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- eedc324400f5f4a31521b2f3c2bc616d1b59a8c931094114f3bd817ff06bb8a9
- Size of remote file:
- 172 MB
- SHA256:
- 4c64330005726b9545173478b87958fc34fdf08b2b9c511bd074fc7db8f8bf3a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.