DynMoE StableLM 1.6B by LINs-lab

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

DynMoE StableLM 1.6B Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
DynMoE StableLM 1.6B (LINs-lab/DynMoE-StableLM-1.6B)

DynMoE StableLM 1.6B Parameters and Internals

Model Type 
MoE model, text generation
Additional Notes 
DynMoE-StableLM activates only a subset of experts dynamically based on the token requirements.
Training Details 
Methodology:
Dynamic Top-k Gating
Training Time:
40 hours
Hardware Used:
8 A100 GPUs
Model Architecture:
MoE with dynamic top-k gating
Release Notes 
Version:
1.0
Date:
2024-05-31
Notes:
Code released.
Version:
1.0
Date:
2024-05-25
Notes:
Checkpoints available.
Version:
1.0
Date:
2024-05-23
Notes:
Paper released.
LLM NameDynMoE StableLM 1.6B
Repository ๐Ÿค—https://huggingface.co/LINs-lab/DynMoE-StableLM-1.6B 
Model Size3.2b
Required VRAM6.4 GB
Updated2025-02-22
MaintainerLINs-lab
Model Typemoe_llava_stablelm
Model Files  5.0 GB: 1-of-2   1.4 GB: 2-of-2   6.4 GB   0.0 GB
Model ArchitectureMoELLaVAStablelmForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.37.0
Tokenizer ClassArcade100kTokenizer
Padding Token<|reg0|>
Vocabulary Size100352
Torch Data Typebfloat16
Errorsreplace

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Data Analysis and Insight Generation  
Text Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227