Instructions to use Muniyaraj/output_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muniyaraj/output_model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muniyaraj/output_model") prompt = "a photo of muniyarajs" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 6fca27bfac84abe44e89be7b2b57ceaf741f283636371c03ac539a6f2b5ab3b2
- Size of remote file:
- 1.59 MB
- SHA256:
- 2bcc4f6346311361a2e2e8f689f546c3e88e2b94862d2314d874bb010f170ee2
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