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
Download image_3.png from Muniyaraj/output_model: direct link, hf CLI and curl.
- Browser
- Download file 1.42 MB
-
https://huggingface.co/Muniyaraj/output_model/resolve/main/image_3.png
- Command line
-
hf download hf://Muniyaraj/output_model/image_3.png
-
curl -L -o image_3.png https://huggingface.co/Muniyaraj/output_model/resolve/main/image_3.png
1.42 MB

- Xet hash:
- 6a9214ca97e69ccaa8c728b2c733abf0d13aec9084ad855bae9a75f5d5082b44
- Size of remote file:
- 1.42 MB
- SHA256:
- 329f2202382ec58e777b84d2b1773cd743ff054d8b85db80203ff6412e6842cf
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