Instructions to use lora-library/wyt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lora-library/wyt with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lora-library/wyt") prompt = "wangyanting" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-200/optimizer.bin from lora-library/wyt: direct link, hf CLI and curl.
- Browser
- Download file 3.49 MB
-
https://huggingface.co/lora-library/wyt/resolve/main/checkpoint-200/optimizer.bin
- Command line
-
hf download hf://lora-library/wyt/checkpoint-200/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/lora-library/wyt/resolve/main/checkpoint-200/optimizer.bin
3.49 MB
- Xet hash:
- e80107210900ba03bbffa1a88c6d1dc7f84fbb59ec2eea136f28d0c7ddbdcb78
- Size of remote file:
- 3.49 MB
- SHA256:
- a4db38efbb61b8d7889b17e785aa9ab9513cb8ef5a93a7e22f3c1e728626c130
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