Instructions to use Sri2901/m_potrait with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Sri2901/m_potrait 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("Sri2901/m_potrait") prompt = "Sample generation" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 9b94d6724c5604a4b5a6b208796722d1e4b518c6fcf605ba1632f0785553fdeb
- Size of remote file:
- 344 MB
- SHA256:
- c7162279176456fb75354f3d9809d6b162d2c731932b7307bd209e2a53fcead1
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