Fix a couple of typos and add some metadata tags
#7
by
pcuenq
HF Staff
- opened
README.md
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library_name: transformers
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---
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# Model Card for Video-LLaVa
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**Model type:**
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Video-LLaVA is an open-source
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Base LLM: [lmsys/vicuna-13b-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5)
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**Model Description:**
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The model can generate interleaving images and videos, despite the absence of image-video pairs in the dataset. Video-LLaVa
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Extensive experiments demonstrate the complementarity of modalities, showcasing significant superiority when compared to models specifically designed for either images or videos.
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<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/videollava_example.png"
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## π Acknowledgement
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* [LLaVA](https://github.com/haotian-liu/LLaVA) The codebase we built upon
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* [Video-ChatGPT](https://github.com/mbzuai-oryx/Video-ChatGPT)
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## π License
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* The majority of this project is released under the Apache 2.0 license as found in the [LICENSE](https://github.com/PKU-YuanGroup/Video-LLaVA/blob/main/LICENSE) file.
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---
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language:
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- en
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library_name: transformers
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license: apache-2.0
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pipeline_tag: video-text-to-text
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datasets:
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- liuhaotian/LLaVA-Pretrain
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- liuhaotian/LLaVA-Instruct-150K
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- luoruipu1/Valley-Instruct-65k
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- lmms-lab/VideoChatGPT
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# Model Card for Video-LLaVa
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**Model type:**
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Video-LLaVA is an open-source multimodal model trained by fine-tuning an LLM on multimodal instruction-following data. It is an auto-regressive language model, based on the transformer architecture.
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Base LLM: [lmsys/vicuna-13b-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5)
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**Model Description:**
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The model can generate text from interleaving images and videos, despite the absence of image-video pairs in the dataset. Video-LLaVa uses an encoder trained for unified visual representation through alignment prior to projection.
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Extensive experiments demonstrate the complementarity of modalities, showcasing significant superiority when compared to models specifically designed for either images or videos.
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<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/videollava_example.png"
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## π Acknowledgement
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* [LLaVA](https://github.com/haotian-liu/LLaVA) The codebase we built upon, LlaVA is an efficient large language model and vision assistant.
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* [Video-ChatGPT](https://github.com/mbzuai-oryx/Video-ChatGPT) We are grateful for the contribution of the evaluation code and dataset.
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## π License
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* The majority of this project is released under the Apache 2.0 license as found in the [LICENSE](https://github.com/PKU-YuanGroup/Video-LLaVA/blob/main/LICENSE) file.
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