Instructions to use iskandre/output2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use iskandre/output2 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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("iskandre/output2") prompt = "a photo of harito cat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- c8908f5577d595c587ee6876415869247b39c085a02865ef695909721aa4329e
- Size of remote file:
- 3.29 MB
- SHA256:
- ca73888ba7a702d39a039ba826a3424bc4c89958f592ed61d241b9a8d59c3879
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