Instructions to use EVA787797/7878787 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EVA787797/7878787 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Shakker-Labs/AWPortrait-FL", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("EVA787797/7878787") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- bc6722b5b9702e93c40d211377569739a11dac899075bf3fef2a586d2c64dd9e
- Size of remote file:
- 172 MB
- SHA256:
- 303373cda55ffc58bee3d1f8ee24c5245d2fc92ad4f8ab27e28d1f4ea9aa67ee
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