Instructions to use doa12/ip2p_lora_without_MoE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use doa12/ip2p_lora_without_MoE with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("doa12/ip2p_lora_without_MoE", 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
- Xet hash:
- 34f405ec129afd9ac7f56f8278f8c8bb7ad3c347235538ee5e44de8711ecdb2c
- Size of remote file:
- 25.7 MB
- SHA256:
- 6910e08f395575a64527801b34a3925e69363f97e863b27e22e2c5b963b7ab55
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