Instructions to use dekes1/cindtcfr15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dekes1/cindtcfr15 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,krea/Krea-2-Raw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("dekes1/cindtcfr15") prompt = "TOK" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 5c05208fe5cb45f1388f4b5a43f2e1abb349da1b518b9b1ade8202497608d3f9
- Size of remote file:
- 195 MB
- SHA256:
- 7a9b20378025aa0a5a1a2796df9313a5b2222ac200c118142554dd30f48c7497
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