Instructions to use jyp96/can with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jyp96/can 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("jyp96/can") prompt = "A photo of sks can in a bucket" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-200/optimizer.bin from jyp96/can: direct link, hf CLI and curl.
- Browser
- Download file 19.1 MB
-
https://huggingface.co/jyp96/can/resolve/main/checkpoint-200/optimizer.bin
- Command line
-
hf download hf://jyp96/can/checkpoint-200/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/jyp96/can/resolve/main/checkpoint-200/optimizer.bin
19.1 MB
- Xet hash:
- 4aa514e3e2b46c2f9a0f18117146812fb8b3a62b2b0b12fcc8aa5afcb7973cdd
- Size of remote file:
- 19.1 MB
- SHA256:
- 79b6d1e160da1fb2ae52333b5d3dfb7260bcd1e501cd8343c199f6c9bd0fe356
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