Instructions to use cuongdev/tnmthu-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/tnmthu-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/tnmthu-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 unet/diffusion_pytorch_model.bin from cuongdev/tnmthu-v3: direct link, hf CLI and curl.
- Browser
- Download file 3.46 GB
-
https://huggingface.co/cuongdev/tnmthu-v3/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://cuongdev/tnmthu-v3/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/cuongdev/tnmthu-v3/resolve/main/unet/diffusion_pytorch_model.bin
3.46 GB
- Xet hash:
- 7d93763ff68ade3fb714add2a4377ce9ab5b1f75e6fae56beea3d2f4521413f9
- Size of remote file:
- 3.46 GB
- SHA256:
- a5778054a7f6ef976bc9cf25a5985d0709b2dab98970897ca0ab4abf61aea157
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