Instructions to use Integrant/Hay6630 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Integrant/Hay6630 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("Integrant/Hay6630") prompt = "hay6630" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- b0386fbdf710599854d52813b52bd417e9a567963927da4072f23fb522f592b8
- Size of remote file:
- 172 MB
- SHA256:
- 41e81ef89f440a68381ce17ee494f4a22116da1c92d8cb6c9486eabc65f088d6
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