Instructions to use xgemstarx/subset_256_step_512_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xgemstarx/subset_256_step_512_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_256_step_512_model") prompt = "a photo of xjiminx" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 0ddf8754de642437c493bfcdfed12a1eaedd54e1a3f95b0a6cb73d67ed5100c6
- Size of remote file:
- 79.2 MB
- SHA256:
- ef7189f370b89c04ae59ba18c19b554d76c266192501e3db3b1c02f3922e0902
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