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.png from tencent/Hy-Nomas-Diffusers: direct link, hf CLI and curl.
- Browser
- Download file 250 kB
-
https://huggingface.co/tencent/Hy-Nomas-Diffusers/resolve/main/assets/method_framework_h.png
- Command line
-
hf download hf://tencent/Hy-Nomas-Diffusers/assets/method_framework_h.png
-
curl -L -o method_framework_h.png https://huggingface.co/tencent/Hy-Nomas-Diffusers/resolve/main/assets/method_framework_h.png
250 kB

- Xet hash:
- 2488c282ccec2eabb3ade9d2a7d9f2300d3d225d88b493322cc254dfc792ffa9
- Size of remote file:
- 250 kB
- SHA256:
- 9f5078c0c14169193c5a7a33b3865ef9cdce905401ec4e37f4d9b7857a7aef37
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