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 transformer/config.json from tencent/Hy-Nomas-Diffusers: direct link, hf CLI and curl.
- Browser
- Download file 477 Bytes
-
https://huggingface.co/tencent/Hy-Nomas-Diffusers/resolve/main/transformer/config.json
- Command line
-
hf download hf://tencent/Hy-Nomas-Diffusers/transformer/config.json
-
curl -L -o config.json https://huggingface.co/tencent/Hy-Nomas-Diffusers/resolve/main/transformer/config.json
477 Bytes
| { | |
| "_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 | |
| } | |