Instructions to use cuongdev/vtthuc-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/vtthuc-v3 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/vtthuc-v3", 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/vtthuc-v3: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/cuongdev/vtthuc-v3/resolve/9cda046116120f8df875edc8dac11b5889f6ad0d/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://cuongdev/vtthuc-v3@9cda046116120f8df875edc8dac11b5889f6ad0d/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/cuongdev/vtthuc-v3/resolve/9cda046116120f8df875edc8dac11b5889f6ad0d/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- 909b52e612561a18d66ac66c4835243ef512179f998eb94411550449b40c4a7f
- Size of remote file:
- 681 MB
- SHA256:
- 0091e8b9930f1268155e015cace405dee07fc707b75c02451a5a6ef7f5a8c51b
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