Instructions to use cuongdev/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cuongdev/test", 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 text_encoder/pytorch_model.bin from cuongdev/test: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/cuongdev/test/resolve/013bfc98a97ffe80f58235aaf3f81bfd8d3099ef/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://cuongdev/test@013bfc98a97ffe80f58235aaf3f81bfd8d3099ef/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/cuongdev/test/resolve/013bfc98a97ffe80f58235aaf3f81bfd8d3099ef/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- 5dee66b629edd1778b35c3c8c3e2f09e12ba291b298eb5731b3c4f1f48a9b0bb
- Size of remote file:
- 681 MB
- SHA256:
- 7d1c642b0190e24cd4f3cd78c40e273724a728b748ca50fd635d59b106f5e65c
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