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:
- a7a46ab8e4c0c680066e41d3ca657e0a05cb9b3daa78d70df6c62639695f5b2b
- Size of remote file:
- 1 kB
- SHA256:
- f05ef39b1cdc763f0d7a75fc4270e2709913ea7bde97046dde7c4f30b695067a
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