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:
- d99bb28b34fa28a2ea9ba62153ba63b9b521aba1e8afc7131b52e757c7bb76a5
- Size of remote file:
- 6.59 MB
- SHA256:
- 6bd676e7d5b6519108f979188fe8f72b8facb0696eacfc5f5d8f91d0107c6017
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.