Instructions to use CLIPP/customcar_tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CLIPP/customcar_tuned with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CLIPP/customcar_tuned", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download unet/diffusion_pytorch_model.bin from CLIPP/customcar_tuned: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/CLIPP/customcar_tuned/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://CLIPP/customcar_tuned/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/CLIPP/customcar_tuned/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 78a2b9261e945cda6074dc20eec9763a60baf470db4a28a7f59d4795a42e96f2
- Size of remote file:
- 3.44 GB
- SHA256:
- c3f1ba2273ebfdc568f0a09976e29fb7c797a6336afe5db45ce611f12bc070e7
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