Instructions to use xgemstarx/subset_8_step_8192_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xgemstarx/subset_8_step_8192_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_8_step_8192_model") prompt = "a photo of xjiminx" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 18b7f4b7c717342cf7bfb483504e1a05f91653122335559091f749fdcb4404d3
- Size of remote file:
- 79.2 MB
- SHA256:
- a249cb113e0b33ef50d648c7e7d21dd50b18dfd8987e1fd22ca36ddfce272b8a
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