Instructions to use rdeinla/test-can-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rdeinla/test-can-3 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("rdeinla/test-can-3") prompt = "A photo of a canola plant rosette with large green leaves. The leaves are ruffled around the edges and have prominent ridges. It is about 35 days old. It grows out of a square box covered with bright blue fabric on a bright blue background" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-2000/optimizer.bin from rdeinla/test-can-3: direct link, hf CLI and curl.
- Browser
- Download file 19.1 MB
-
https://huggingface.co/rdeinla/test-can-3/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://rdeinla/test-can-3/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/rdeinla/test-can-3/resolve/main/checkpoint-2000/optimizer.bin
19.1 MB
- Xet hash:
- 8384f080d0a496864dc760fe764a3b02b68f224a45063de3485121815adfd5ae
- Size of remote file:
- 19.1 MB
- SHA256:
- 95189aad088808be3598fc47cab8d90318c290bfa3f85060a45ce4e862f978eb
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