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Imagebind Huge by nielsr

 »  All LLMs  »  nielsr  »  Imagebind Huge   URL Share it on

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  Endpoints compatible   Model hub mixin   Multimodal   Pytorch model hub mixin   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/nielsr/imagebind-huge 

Imagebind Huge Benchmarks

LLME Score: 0.14475
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Imagebind Huge (nielsr/imagebind-huge)
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Imagebind Huge Parameters and Internals

Model Type 
multimodal
Use Cases 
Areas:
Research, Commercial applications
Applications:
Cross-modal retrieval, Composing modalities with arithmetic, Cross-modal detection, Cross-modal generation
Primary Use Cases:
Multi-modal embeddings for images, text, audio, depth, thermal, and IMU data
Additional Notes 
Model allows extraction and comparison of features across modalities.
Input Output 
Accepted Modalities:
text, image, audio, depth, thermal, IMU data
LLM NameImagebind Huge
Repository 🤗https://huggingface.co/nielsr/imagebind-huge 
Model Size1.2b
Required VRAM4.8 GB
Updated2025-09-23
Maintainernielsr
Model Files  4.8 GB
Model ArchitectureAutoModel
Licensecc-by-nc-sa-4.0

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Note: green Score (e.g. "73.2") means that the model is better than nielsr/imagebind-huge.

Rank the Imagebind Huge Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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