Instructions to use Skywork/Matrix-Game with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Skywork/Matrix-Game with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Skywork/Matrix-Game", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
File size: 785 Bytes
c276cff | 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 27 28 29 30 31 32 33 | {
"_class_name": "AutoencoderKLCausal3D",
"_diffusers_version": "0.4.2",
"act_fn": "silu",
"block_out_channels": [
128,
256,
512,
512
],
"down_block_types": [
"DownEncoderBlockCausal3D",
"DownEncoderBlockCausal3D",
"DownEncoderBlockCausal3D",
"DownEncoderBlockCausal3D"
],
"in_channels": 3,
"latent_channels": 16,
"layers_per_block": 2,
"norm_num_groups": 32,
"out_channels": 3,
"sample_size": 256,
"sample_tsize": 64,
"up_block_types": [
"UpDecoderBlockCausal3D",
"UpDecoderBlockCausal3D",
"UpDecoderBlockCausal3D",
"UpDecoderBlockCausal3D"
],
"scaling_factor": 0.476986,
"time_compression_ratio": 4,
"mid_block_add_attention": true
} |