Instructions to use xgemstarx/subset_64_step_16384_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xgemstarx/subset_64_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_64_step_16384_model") prompt = "a photo of xjiminx" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 09aa106dfa554b52ee3d99971aaf7381ebdd7ce6324e49a801b4f2543fc109d0
- Size of remote file:
- 79.2 MB
- SHA256:
- f1b1e6c273e2609cdd4a8df135e804e8bb911e083983e48bbe5e4fb2b30d0e7d
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