Instructions to use callumstackk/cstack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use callumstackk/cstack 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("callumstackk/cstack") prompt = "Cstack" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 6d7b35147f7cb97dd3fcd6de6703d6659ec23735b49dc8fe379dadbbdd4a7947
- Size of remote file:
- 172 MB
- SHA256:
- fbe5b862d27722abaaf892b887e2792193d003565e1f98ffd4ddc6031fa56187
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