Instructions to use ItsJayQz/Valorant_Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ItsJayQz/Valorant_Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ItsJayQz/Valorant_Diffusion", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit History
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add gradio demo
5385512
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (c7e07aa8b5e5eabe5d3873102596c865b1168537)5129ce9 -
Upload Valorant_Diffusion_valorant_style.ckpt
Upload checkpoint.99be3c7 -
Update README.md
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initial commit
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