Instructions to use camus-ng/lora-trained-xl-cory-10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use camus-ng/lora-trained-xl-cory-10 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("camus-ng/lora-trained-xl-cory-10") prompt = "a photo of <ntvc> man" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download image_1.png from camus-ng/lora-trained-xl-cory-10: direct link, hf CLI and curl.
- Browser
- Download file 1.14 MB
-
https://huggingface.co/camus-ng/lora-trained-xl-cory-10/resolve/main/image_1.png
- Command line
-
hf download hf://camus-ng/lora-trained-xl-cory-10/image_1.png
-
curl -L -o image_1.png https://huggingface.co/camus-ng/lora-trained-xl-cory-10/resolve/main/image_1.png
1.14 MB

- Xet hash:
- d377ca64b495cfe087a4ead862db0e879cb5684fa60b2b64b111f38cd835f252
- Size of remote file:
- 1.14 MB
- SHA256:
- 2875556899d128cef8787febebdb0e696e21ed57a057e37856902d33306ad705
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