Instructions to use Mujeeb603/lora-training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Mujeeb603/lora-training 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("Mujeeb603/lora-training") prompt = "unconditional (blank prompt)" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 2b15a5d5c2ef0422688adf0b4c816aa6fb3a86a6b9c583cb9b1bce2585c53ab7
- Size of remote file:
- 28.5 MB
- SHA256:
- 617ea1fe3daf439fb6ac10f13d5f66539ced58dd354d671886569de5c062abb4
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