Instructions to use habulaj/dasascas with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use habulaj/dasascas with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("habulaj/dasascas") prompt = "fdasd" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 0f0348ab955b18d4cdbeff4112a3ab35ac660ac0957c5de7d0ef7c256642ae90
- Size of remote file:
- 15 MB
- SHA256:
- 6fd130088ded1be227b14be8cd9d8f71f0af945cf15df9e88436a027fa3b56aa
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