Instructions to use AlexanderLab/JCHHD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlexanderLab/JCHHD 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("AlexanderLab/JCHHD") prompt = "JCHHD" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 4e6ddead98c2c24fd207d5f2676026e399d4c7f41a769218602b3459906679e2
- Size of remote file:
- 344 MB
- SHA256:
- c2387884e2edcf961033751fc901bc07b0e769f33bf357ea3d354c21ce3d6631
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