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
- Draw Things
- DiffusionBee
- Xet hash:
- a40e1af17d39518c28ce9c145be1ff80ab6db1e8ff1b7278bb14c7cfddb94564
- Size of remote file:
- 6.59 MB
- SHA256:
- e74deaafae6a610ef4fa3ecf9cf27971b0309b10ea37fe22930e8ce39c1f265f
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