Diffusers
Safetensors
PyTorch
hy-nomas
world-model
video-generation
interactive-video-generation
camera-control
autoregressive
diffusion-transformer
Instructions to use tencent/Hy-Nomas-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tencent/Hy-Nomas-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tencent/Hy-Nomas-Diffusers", 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 assets/method_framework_h_cn.png from tencent/Hy-Nomas-Diffusers: direct link, hf CLI and curl.
- Browser
- Download file 254 kB
-
https://huggingface.co/tencent/Hy-Nomas-Diffusers/resolve/main/assets/method_framework_h_cn.png
- Command line
-
hf download hf://tencent/Hy-Nomas-Diffusers/assets/method_framework_h_cn.png
-
curl -L -o method_framework_h_cn.png https://huggingface.co/tencent/Hy-Nomas-Diffusers/resolve/main/assets/method_framework_h_cn.png
254 kB

- Xet hash:
- ac1d2969e95236b7cd09d78788ff170dae413e2df65a468ef28bf26059ccb8f8
- Size of remote file:
- 254 kB
- SHA256:
- 0927c8c7d9983e1605d68b4d9a887b4f626400f77d020e337ac53da0d295d10c
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