DynMoE Qwen 1.8B by LINs-lab

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  Arxiv:2405.14297   Autotrain compatible   Custom code   Endpoints compatible   Image-text-to-text   Moe   Moe llava qwen   Pytorch   Region:us   Safetensors   Sharded   Tensorflow

DynMoE Qwen 1.8B Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
DynMoE Qwen 1.8B (LINs-lab/DynMoE-Qwen-1.8B)

DynMoE Qwen 1.8B Parameters and Internals

Model Type 
MoE, transformer
Additional Notes 
The model activates 2.2B out of 3.1B parameters on average.
Training Details 
Methodology:
dynamic top-k gating, adaptive training process
Training Time:
40 hours
Hardware Used:
8 A100 GPUs
Model Architecture:
Dynamic Mixture of Experts (DynMoE) with dynamic top-k gating
Release Notes 
Version:
2024.05.31
Notes:
Code release.
Version:
2024.05.25
Notes:
Checkpoints available.
Version:
2024.05.23
Notes:
Paper release.
LLM NameDynMoE Qwen 1.8B
Repository ๐Ÿค—https://huggingface.co/LINs-lab/DynMoE-Qwen-1.8B 
Model Size3.4b
Required VRAM5.7 GB
Updated2025-02-22
MaintainerLINs-lab
Model Typemoe_llava_qwen
Model Files  5.0 GB: 1-of-2   0.7 GB: 2-of-2   4.9 GB   0.0 GB
Model ArchitectureLlavaQWenForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.37.0
Tokenizer ClassQWenTokenizer
Padding Token<|extra_0|>
Vocabulary Size151936
Torch Data Typebfloat16

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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 v20241227