Instructions to use dashabalashova/trained-sd3-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dashabalashova/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-3.5-medium", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("dashabalashova/trained-sd3-lora") prompt = "A photo of sks dog in a bucket" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-500/optimizer.bin from dashabalashova/trained-sd3-lora: direct link, hf CLI and curl.
- Browser
- Download file 19.1 MB
-
https://huggingface.co/dashabalashova/trained-sd3-lora/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://dashabalashova/trained-sd3-lora/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/dashabalashova/trained-sd3-lora/resolve/main/checkpoint-500/optimizer.bin
19.1 MB
- Xet hash:
- d699c5bd44a0e306adc95e331948703aa512404dac18685f76b45a1803ee0b37
- Size of remote file:
- 19.1 MB
- SHA256:
- 212285d2b09c1ae36fb52f8e6ecf5d2eea1ae388c39dedcf5c26d13105e286f9
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