Instructions to use allen93/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use allen93/output 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("allen93/output") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- d103aacf9c68d9255fd62c4e1ea9b4d33a08ff92def529ea3b1da53a3a87de1b
- Size of remote file:
- 375 kB
- SHA256:
- 080be50f8aeffe254276ed71029e6cdecfe79cc2f27459e67b32f597427d8cdb
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