Instructions to use xgemstarx/subset_128_step_16384_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xgemstarx/subset_128_step_16384_model 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("xgemstarx/subset_128_step_16384_model") prompt = "a photo of xjiminx" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- d330e97687652ae3b84d66f06c39711ec132f5d58fed40e630e99c71a90a8380
- Size of remote file:
- 79.2 MB
- SHA256:
- 6990ccbea89915f2b1837649e4380751b0dc14a579a020be804d0e3125b042ed
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