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:
- ef81ada34a28c4fb43daf0d03fad3a8aaf12b02e69f14b96dab4bf35af26ff62
- Size of remote file:
- 79.2 MB
- SHA256:
- 0d8ccee9eb4892732f8f06a39691f0357ded5e472504452c7c71c84115996115
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