Instructions to use hp-l33/ARPG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hp-l33/ARPG with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hp-l33/ARPG", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Add pipeline tag, library name, project page, and link to code
#1
by nielsr HF Staff - opened
This PR adds the pipeline_tag as unconditional-image-generation and library_name as pytorch to the model card metadata. It also adds a link to the project page and the Github repository.
hp-l33 changed pull request status to merged