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/text_encoder/pytorch_model.bin from camenduru/testA: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/camenduru/testA/resolve/main/output_dir_650/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://camenduru/testA/output_dir_650/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/camenduru/testA/resolve/main/output_dir_650/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 4a6f48ffc564d75ce9ba3b97bbc8190900991615f45911dcf03f31e4f5ef7014
- Size of remote file:
- 246 MB
- SHA256:
- 353aa189c6da3dbd16433b0a7271a82eb14a6ab142c0381aa0dcaab648aad2ba
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