Instructions to use 22Plaruno/CW_MODEL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 22Plaruno/CW_MODEL with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("22Plaruno/CW_MODEL", 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
Download checkpoint-3000/optimizer.bin from 22Plaruno/CW_MODEL: direct link, hf CLI and curl.
- Browser
- Download file 910 MB
-
https://huggingface.co/22Plaruno/CW_MODEL/resolve/main/checkpoint-3000/optimizer.bin
- Command line
-
hf download hf://22Plaruno/CW_MODEL/checkpoint-3000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/22Plaruno/CW_MODEL/resolve/main/checkpoint-3000/optimizer.bin
910 MB
- Xet hash:
- 59684cfc47a138309bec1d8fbf70029af7c15e928bc78c004572d84f6fe634d6
- Size of remote file:
- 910 MB
- SHA256:
- 69f7872a6f539e43b1f1158cf232eb675776d5390d1f7b4a793eb15d9faa4162
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