Instructions to use cuongdev/cothu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/cothu 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/cothu", 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/cothu: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/cuongdev/cothu/resolve/226cc61f613eb7810a8b8d4e2f02aa5eb2bee4e4/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://cuongdev/cothu@226cc61f613eb7810a8b8d4e2f02aa5eb2bee4e4/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/cuongdev/cothu/resolve/226cc61f613eb7810a8b8d4e2f02aa5eb2bee4e4/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- 3902af9d877c585162ef9476ff5e53f7833c857510f75fbed5b2a5d8720d8ff8
- Size of remote file:
- 681 MB
- SHA256:
- 722796bdf4a25e38df07736eead1b42a72340f5600c6a9ab0be0b828f939dc5f
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