Instructions to use Adminhuggingface/OUTPUTA_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Adminhuggingface/OUTPUTA_2 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("Adminhuggingface/OUTPUTA_2") 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:
- 862c4b14e5fc13f2aa9fff3fc56d8d478bbe325bfd77ef8c0bbd3abdf247c41f
- Size of remote file:
- 6.59 MB
- SHA256:
- 16d675a711d0f9350f5a0fa7c00e6b9d1c811230a6f91f679a57b0ee3b5a5859
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