Instructions to use nob/lora-trained-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nob/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("nob/lora-trained-xl") prompt = "sks fundus" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-7500/optimizer.bin from nob/lora-trained-xl: direct link, hf CLI and curl.
- Browser
- Download file 47.4 MB
-
https://huggingface.co/nob/lora-trained-xl/resolve/main/checkpoint-7500/optimizer.bin
- Command line
-
hf download hf://nob/lora-trained-xl/checkpoint-7500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/nob/lora-trained-xl/resolve/main/checkpoint-7500/optimizer.bin
47.4 MB
- Xet hash:
- 5adff3119091ab84c55a6a95c09c91bec27887e28def638d2a03d654cd0f8877
- Size of remote file:
- 47.4 MB
- SHA256:
- e2704a15aaabdb70012bd39d58be3140dd5c1d228322cf0a117ba94b82d1dddc
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