Instructions to use B4100/ddinsert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use B4100/ddinsert with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wikeeyang/Flux2-Klein-9B-True-V2", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("B4100/ddinsert") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 5722342d3216c705ccaaa032173e4829208b6dd47833fcdf58cd23664334e223
- Size of remote file:
- 1.09 MB
- SHA256:
- 18544c36c6ec76753b5dc2c14c3e1c22b2cef248ebfc33a02061b080cf2288aa
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