Instructions to use harshvardhan96/output-results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use harshvardhan96/output-results 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("harshvardhan96/output-results") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- e0810d6a4c41b65f3859000a1e861442f3d6e1b5c14e617319e5c3f4abe79357
- Size of remote file:
- 6.59 MB
- SHA256:
- 041082957135fa19225d30afdd8778eed64de66e368a0569cf6bf72ca3abb5d9
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