Instructions to use PSJJ/project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PSJJ/project with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("PSJJ/project") prompt = "Please generate a realistic human image with clear facial features, natural body proportions, and diverse poses. The generated person should resemble a genuine photograph with realistic lighting, clothing, and background. Pay attention to details like facial expressions, hair, and skin texture. Thank you!" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- a6746b1b8831b46bd7a8a04e0fd200c636a825c505adc0d6ef5b8ba5a6ac0fb5
- Size of remote file:
- 6.64 MB
- SHA256:
- 493578a4e8eadf4336654a708794dfbb4ff577ebc52be6b97e5766e1a2320030
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