Instructions to use xgemstarx/profile_model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xgemstarx/profile_model2 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("xgemstarx/profile_model2") prompt = "a photo of xjiminx" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 1a097c65f3844eed2833565a7d193ed1f1af4e02f567613c950c83f5399f0e95
- Size of remote file:
- 79.2 MB
- SHA256:
- faf1a6b12fa99f671efecb885302ae4334a5ed9a93ebe1a3233ad63a826eed5d
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