Instructions to use ByteDance/BindWeave with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ByteDance/BindWeave 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("ByteDance/BindWeave", 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
lizhaoyang commited on
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Add README
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README.md
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It achieves cross-modal integration via entity grounding and representation alignment, leveraging the MLLM to parse complex prompts and produce subject-aware hidden states that condition the DiT for high-fidelity generation.
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### OpenS2V-Eval Performance 🏆
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BindWeave achieves a solid score of 57.61 on the OpenS2V-Eval benchmark, highlighting its robust capabilities across multiple evaluation dimensions and demonstrating competitive performance against several leading open-source and commercial systems.
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| Model | TotalScore↑ | AestheticScore↑ | MotionSmoothness↑ | MotionAmplitude↑ | FaceSim↑ | GmeScore↑ | NexusScore↑ | NaturalScore↑ |
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It achieves cross-modal integration via entity grounding and representation alignment, leveraging the MLLM to parse complex prompts and produce subject-aware hidden states that condition the DiT for high-fidelity generation.
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### OpenS2V-Eval Performance 🏆
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BindWeave achieves a solid score of 57.61 on the [OpenS2V-Eval](https://huggingface.co/spaces/BestWishYsh/OpenS2V-Eval) benchmark, highlighting its robust capabilities across multiple evaluation dimensions and demonstrating competitive performance against several leading open-source and commercial systems.
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| Model | TotalScore↑ | AestheticScore↑ | MotionSmoothness↑ | MotionAmplitude↑ | FaceSim↑ | GmeScore↑ | NexusScore↑ | NaturalScore↑ |
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