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:
- 69d9d58529db4503d89a9007667e14acbaccf812ec44aa4035adbb17e10163f3
- Size of remote file:
- 344 MB
- SHA256:
- 02eb3f0779269eebb9b89a233f4dd97dd4482820b92737aaa9101f8baafe99b5
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