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:
- 6ec27c9d55e2b4a47b9230f1b49ebee77e423e4b1f533bf65f571c188e699336
- Size of remote file:
- 79.2 MB
- SHA256:
- 8ffeba8813408545985590ddf57fc12ad0c851efc3ebe53219fb36a911edc3bf
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