Instructions to use camenduru/testA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use camenduru/testA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("camenduru/testA", 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 output_dir_650/vae/diffusion_pytorch_model.bin from camenduru/testA: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/camenduru/testA/resolve/main/output_dir_650/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://camenduru/testA/output_dir_650/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/camenduru/testA/resolve/main/output_dir_650/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 9fc476ffc7cdf742fccd204d9b61cf3fd5863437eb368ef781cba4116c317047
- Size of remote file:
- 335 MB
- SHA256:
- 67cc45e9b0bf8ab90f2e3a4ef8f5c5ce5589098bae089b7295ac559de238398e
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