Instructions to use lovelyjaban/trained-sd3-lora-test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lovelyjaban/trained-sd3-lora-test2 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("lovelyjaban/trained-sd3-lora-test2") prompt = "A photo of a t-shirt with hmwrks drawing style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-102000/scheduler.bin from lovelyjaban/trained-sd3-lora-test2: direct link, hf CLI and curl.
- Browser
- Download file 1 kB
-
https://huggingface.co/lovelyjaban/trained-sd3-lora-test2/resolve/main/checkpoint-102000/scheduler.bin
- Command line
-
hf download hf://lovelyjaban/trained-sd3-lora-test2/checkpoint-102000/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/lovelyjaban/trained-sd3-lora-test2/resolve/main/checkpoint-102000/scheduler.bin
1 kB
- Xet hash:
- f8b70f80a10d89001dc81f0be7329f65a9aaa357ff362b6f2f7747b100b75b29
- Size of remote file:
- 1 kB
- SHA256:
- d15d97547f064a677e75a47f4890bf28608a4c5179a81a6b1c3031d26f19b706
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