Instructions to use jcjo/cat3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jcjo/cat3 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-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jcjo/cat3") prompt = "a photo of yeonpickPJY grey and green eye cat" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-717/optimizer.bin from jcjo/cat3: direct link, hf CLI and curl.
- Browser
- Download file 20.1 MB
-
https://huggingface.co/jcjo/cat3/resolve/main/checkpoint-717/optimizer.bin
- Command line
-
hf download hf://jcjo/cat3/checkpoint-717/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/jcjo/cat3/resolve/main/checkpoint-717/optimizer.bin
20.1 MB
- Xet hash:
- 7933abe8011da8ff7850c7c76225a19b73f3d97ca398fd49e3117d20bad6d57c
- Size of remote file:
- 20.1 MB
- SHA256:
- b529f67ce8552d622e98eed468a69f92f80fb02cee2803d51d0052c63efb60a4
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