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
File size: 477 Bytes
a1ae04d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"_class_name": "HyNomasTransformer3DModel",
"_diffusers_version": "0.42.0.dev0",
"attention_head_dim": 128,
"camera_attention_dim": 1024,
"camera_embed_dim": 128,
"camera_num_attention_heads": 16,
"camera_rope_axes_dim": [
8,
28,
28
],
"in_channels": 32,
"mlp_ratio": 4.0,
"num_attention_heads": 16,
"num_layers": 54,
"out_channels": 32,
"rope_axes_dim": [
16,
56,
56
],
"rope_theta": 256.0,
"text_embed_dim": 3584
}
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