Instructions to use codemanCheng/lora-trained-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codemanCheng/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("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("codemanCheng/lora-trained-xl") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download pytorch_lora_weights.bin from codemanCheng/lora-trained-xl: direct link, hf CLI and curl.
- Browser
- Download file 23.7 MB
-
https://huggingface.co/codemanCheng/lora-trained-xl/resolve/main/pytorch_lora_weights.bin
- Command line
-
hf download hf://codemanCheng/lora-trained-xl/pytorch_lora_weights.bin
-
curl -L -o pytorch_lora_weights.bin https://huggingface.co/codemanCheng/lora-trained-xl/resolve/main/pytorch_lora_weights.bin
23.7 MB
- Xet hash:
- 412a278e7f7f64cc0c6fe2029c519d804bb8adc304ff60a892d4369340cced38
- Size of remote file:
- 23.7 MB
- SHA256:
- eb4cb3667de74e72a4a84eb58d2fbac99c24ad048e23630aaf6bd671bd543b48
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