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:
- e8255401c3cfb5f40484e682337beac45a0f618518a68858fa5eb97085017e80
- Size of remote file:
- 344 MB
- SHA256:
- 6828a8c5b13fff7ec6b056ac2f6c553a89c0ef9a1ba6306d77e25198cbb8d0f8
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