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:
- 1398008d10757a279f323bc8739606c302dc762fd97b81d28eb8faa0ee49dbaa
- Size of remote file:
- 1.65 MB
- SHA256:
- 13808ac271a2c13df5ed854581cb6bb278581a794a395e8f4136d62b251a5517
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