Instructions to use Amyww/2000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Amyww/2000 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Datou1111/shou_xin", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Amyww/2000") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 06bf263b961a7af1917704ab7f2e712cecbdaebfb6b3568e960be4597dadb14c
- Size of remote file:
- 3.72 kB
- SHA256:
- 60906d73ec23dafb2e3fca18ca7458762b8240e2e46faa5ea487e5783d906993
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