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", 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:
- 30ec886b8c231738484eea882fba47e154206f362e2b65fb2a4b1cc89270cd7b
- Size of remote file:
- 1.72 GB
- SHA256:
- 41003fc157f6c4a4607328b91e14c756bf2ffc595f29b256a87db520f5a5f999
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