Instructions to use DarkMoonDragon/trained-sd3-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DarkMoonDragon/trained-sd3-lora 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-3-medium-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("DarkMoonDragon/trained-sd3-lora") prompt = "a photo of TOK yarn art dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-1500/scheduler.bin from DarkMoonDragon/trained-sd3-lora: direct link, hf CLI and curl.
- Browser
- Download file 1.47 kB
-
https://huggingface.co/DarkMoonDragon/trained-sd3-lora/resolve/main/checkpoint-1500/scheduler.bin
- Command line
-
hf download hf://DarkMoonDragon/trained-sd3-lora/checkpoint-1500/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/DarkMoonDragon/trained-sd3-lora/resolve/main/checkpoint-1500/scheduler.bin
1.47 kB
- Xet hash:
- 411bcde57b7d831e54f72a01ef38c22b0310877590eefee9af82ecff69f5b7c6
- Size of remote file:
- 1.47 kB
- SHA256:
- 1ad780c6fc7b21137c2cb65789e231b474fe0bf0ee3f2be2e2151ebccc55e720
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