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:
- c1321d1c0a9b52d0e1e0cc897ad0da300ad54f4336ca0658d1a60021c646f195
- Size of remote file:
- 23.7 MB
- SHA256:
- d639b548018f4a495466789b340f2cfabee2f6db1a8ef696b0f7ebd33f93dd00
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