Instructions to use QFun/lora-trained-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use QFun/lora-trained-xl 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-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("QFun/lora-trained-xl") prompt = "a photo of rgb5_mix woman in front of the green curtain" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-2000/optimizer.bin from QFun/lora-trained-xl: direct link, hf CLI and curl.
- Browser
- Download file 47.4 MB
-
https://huggingface.co/QFun/lora-trained-xl/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://QFun/lora-trained-xl/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/QFun/lora-trained-xl/resolve/main/checkpoint-2000/optimizer.bin
47.4 MB
- Xet hash:
- e017c325db25dc6b7341872eb310af432b6a4ad6ec8c9777853bb963a17653b7
- Size of remote file:
- 47.4 MB
- SHA256:
- 1750342f4282ce809f51efa9f19f37ecce665e3585d4b8c84aa5be0a7a336af9
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