Instructions to use Rand000mGuy/muscleK with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Rand000mGuy/muscleK with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Rand000mGuy/muscleK") prompt = "Screenshot" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- bc91b6990fa96cd62e55690cd0c4a36566b2d31c58ff5201d1f8cda3b8cf2604
- Size of remote file:
- 57.2 MB
- SHA256:
- 8107cb766ca93409ae36de101f67ea731fdd367aeb3a13e69d33e42567040e90
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