Instructions to use iskandre/output1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use iskandre/output1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("iskandre/output1") prompt = "a photo of Haro" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 4d6b0798cf58c9a6d0774bbd7e6b93f22e27d66ced22aabe64247097b1de5eaa
- Size of remote file:
- 6.59 MB
- SHA256:
- 7393197c27a56b948aadeb52a3578ceb4653ced31264d3dcee5a5008ea35ba27
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