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UniWorld-V1
- huggingface.co
Updated Jun 13, 2025
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EmailClick to copy linkLink copiedCitelinbin (2025). UniWorld-V1 [Dataset]. https://huggingface.co/datasets/LanguageBind/UniWorld-V1Dataset updatedJun 13, 2025AuthorslinbinLicenseMIT Licensehttps://opensource.org/licenses/MIT
License information was derived automaticallyDescriptionThe Geneval-style dataset is sourced from BLIP3o-60k.
This dataset is presented in the paper: UniWorld: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation More details can be found in UniWorld-V1
Data preparationDownload the data from LanguageBind/UniWorld-V1. The dataset consists of two parts: source images and annotation JSON files. Prepare a data.txt file in the following format:
The first column is the root path to the image.
The second… See the full description on the dataset page: https://huggingface.co/datasets/LanguageBind/UniWorld-V1.
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Data from: Video-Bench
- huggingface.co
Updated Dec 2, 2023+ more versionsShareFacebookTwitterEmailClick to copy linkLink copiedCitelinbin (2023). Video-Bench [Dataset]. https://huggingface.co/datasets/LanguageBind/Video-BenchDataset updatedDec 2, 2023AuthorslinbinLicenseApache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automaticallyDescriptionLanguageBind/Video-Bench dataset hosted on Hugging Face and contributed by the HF Datasets community
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MoE-LLaVA
- huggingface.co
Updated Jan 30, 2024ShareFacebookTwitterEmailClick to copy linkLink copiedCitelinbin (2024). MoE-LLaVA [Dataset]. https://huggingface.co/datasets/LanguageBind/MoE-LLaVACroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.Dataset updatedJan 30, 2024AuthorslinbinLicenseApache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automaticallyDescriptionMoE-LLaVA: Mixture of Experts for Large Vision-Language Models If you like our project, please give us a star ⭐ on GitHub for latest update.
📰 News[2024.01.30] The paper is released. [2024.01.27] 🤗Hugging Face demo and all codes & datasets are available now! Welcome to watch 👀 this repository for the latest updates.
😮 HighlightsMoE-LLaVA shows excellent performance in multi-modal learning.
🔥 High performance, but with fewer… See the full description on the dataset page: https://huggingface.co/datasets/LanguageBind/MoE-LLaVA. - h
VIDAL-Depth-Thermal
- huggingface.co
Updated Jan 4, 2024ShareFacebookTwitterEmailClick to copy linkLink copiedCitelinbin (2024). VIDAL-Depth-Thermal [Dataset]. https://huggingface.co/datasets/LanguageBind/VIDAL-Depth-ThermalDataset updatedJan 4, 2024AuthorslinbinLicenseMIT Licensehttps://opensource.org/licenses/MIT
License information was derived automaticallyDescription【ICLR 2024 🔥】LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment If you like our project, please give us a star ⭐ on GitHub for latest update.
📰 News[2024.01.27] 👀👀👀 Our MoE-LLaVA is released! A sparse model with 3B parameters outperformed the dense model with 7B parameters. [2024.01.16] 🔥🔥🔥 Our LanguageBind has been accepted at ICLR 2024! We earn the score of 6(3)8(6)6(6)6(6) here. [2023.12.15] 💪💪💪 We… See the full description on the dataset page: https://huggingface.co/datasets/LanguageBind/VIDAL-Depth-Thermal.
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Cambrian737k
- huggingface.co
Updated Mar 20, 2025ShareFacebookTwitterEmailClick to copy linkLink copiedCitelinbin (2025). Cambrian737k [Dataset]. https://huggingface.co/datasets/LanguageBind/Cambrian737kDataset updatedMar 20, 2025AuthorslinbinLicenseApache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automaticallyDescriptionLanguageBind/Cambrian737k dataset hosted on Hugging Face and contributed by the HF Datasets community
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StyleVideoDataSet
- huggingface.co
Updated Nov 27, 2025+ more versionsShareFacebookTwitterEmailClick to copy linkLink copiedCitelinbin (2025). StyleVideoDataSet [Dataset]. https://huggingface.co/datasets/LanguageBind/StyleVideoDataSetDataset updatedNov 27, 2025AuthorslinbinDescriptionLanguageBind/StyleVideoDataSet dataset hosted on Hugging Face and contributed by the HF Datasets community
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LLMBind
- huggingface.co
Updated Jun 16, 2024ShareFacebookTwitterEmailClick to copy linkLink copiedCitelinbin (2024). LLMBind [Dataset]. https://huggingface.co/datasets/LanguageBind/LLMBindCroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.Dataset updatedJun 16, 2024AuthorslinbinDescriptionLanguageBind/LLMBind dataset hosted on Hugging Face and contributed by the HF Datasets community
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TinyLLaVA-Video-v1-training-data
- huggingface.co
Updated Apr 14, 2025ShareFacebookTwitterEmailClick to copy linkLink copiedCiteZhang Xingjian (2025). TinyLLaVA-Video-v1-training-data [Dataset]. https://huggingface.co/datasets/Zhang199/TinyLLaVA-Video-v1-training-dataDataset updatedApr 14, 2025AuthorsZhang XingjianLicenseApache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automaticallyDescriptionTinyLLaVA-Video
This dataset combines data from multiple sources for pre-training and fine-tuning. Pretrain Data: Four subsets of LLaVA-Video-178K (0_30_s_academic_v0_1, 30_60_s_academic_v0_1, 0_30_s_youtube_v0_1, 30_60_s_youtube_v0_1), supplemented with filtered Video-LLaVA data (https://huggingface.co/datasets/LanguageBind/Video-LLaVA) and data from Valley (https://github.com/RupertLuo/Valley). The video data can be downloaded from the linked datasets, and cleaned annotations are provided… See the full description on the dataset page: https://huggingface.co/datasets/Zhang199/TinyLLaVA-Video-v1-training-data.
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FacebookTwitterEmailMIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
The Geneval-style dataset is sourced from BLIP3o-60k.
This dataset is presented in the paper: UniWorld: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation More details can be found in UniWorld-V1
Data preparation
Download the data from LanguageBind/UniWorld-V1. The dataset consists of two parts: source images and annotation JSON files. Prepare a data.txt file in the following format:
The first column is the root path to the image.
The second… See the full description on the dataset page: https://huggingface.co/datasets/LanguageBind/UniWorld-V1.