Instructions to use xgemstarx/subset_1024_step_8192_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xgemstarx/subset_1024_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_1024_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:
- f5eb377aae093697e4e41c18705253e4b230bb762f45887e1a958049151697cc
- Size of remote file:
- 79.2 MB
- SHA256:
- d22e234b8f0f8a9b7d980d0d065c92e372999410e1c07a8a7aad98c58f04f88e
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