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-100/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-100/optimizer.bin
- Command line
-
hf download hf://jyp96/can/checkpoint-100/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/jyp96/can/resolve/main/checkpoint-100/optimizer.bin
19.1 MB
- Xet hash:
- 84ae8a9207d230dc7acd17addd517e7b0340fa432e11fe7e96041ead7d0454e7
- Size of remote file:
- 19.1 MB
- SHA256:
- 7f3406409e2ec53e199418346c07b8867354580c8aa3bd42916f183dcd39e3f7
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