Instructions to use Skywork/Matrix-Game-2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Skywork/Matrix-Game-2.0 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-2.0", 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
Upload model_index.json with huggingface_hub
Browse files- model_index.json +28 -0
model_index.json
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{
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"_class_name": "MatrixGame2I2VPipeline",
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"_diffusers_version": "0.33.1",
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"scheduler": [
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"diffusers",
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"FlowUniPCMultistepScheduler"
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],
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"transformer": [
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"diffusers",
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"MatrixGame3WanModel"
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],
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"vae": [
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"diffusers",
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"AutoencoderKLWan"
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],
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"text_encoder": [
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"transformers",
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"UMT5EncoderModel"
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],
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"tokenizer": [
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"transformers",
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"T5TokenizerFast"
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],
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"light_vae": [
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"diffusers",
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"AutoencoderKLWan"
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]
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}
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