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:
- bf57d844ec02fccac4a01f52028290d698ca1fb5e6c8776a9d97ba2b1101b57d
- Size of remote file:
- 350 MB
- SHA256:
- 4ef84e896dbb3a0d4a99dcaedad2402ea3f8d26c9d05553da77657d35f2e6cae
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