MoE LLaVA Phi2 2.7B 4e by LanguageBind

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  Arxiv:2311.10122   Arxiv:2401.15947   Autotrain compatible   Custom code   Endpoints compatible   Moe   Moe llava phi   Region:us   Safetensors   Sharded   Tensorflow

MoE LLaVA Phi2 2.7B 4e Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MoE LLaVA Phi2 2.7B 4e (LanguageBind/MoE-LLaVA-Phi2-2.7B-4e)

MoE LLaVA Phi2 2.7B 4e Parameters and Internals

Model Type 
vision-language, multimodal
Additional Notes 
MoE-LLaVA shows excellent performance in multi-modal learning with fewer parameters.
Training Details 
Methodology:
A simple MoE tuning stage was added.
Training Time:
2 days
Hardware Used:
8 V100 GPUs
LLM NameMoE LLaVA Phi2 2.7B 4e
Repository ๐Ÿค—https://huggingface.co/LanguageBind/MoE-LLaVA-Phi2-2.7B-4e 
Model Size5.6b
Required VRAM11.2 GB
Updated2025-02-22
MaintainerLanguageBind
Model Typemoe_llava_phi
Model Files  5.0 GB: 1-of-3   5.0 GB: 2-of-3   1.2 GB: 3-of-3
Model ArchitectureMoELLaVAPhiForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.36.2
Tokenizer ClassCodeGenTokenizer
Padding Token<|extra_0|>
Vocabulary Size51200
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than LanguageBind/MoE-LLaVA-Phi2-2.7B-4e.

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227