LLaMA MoE V1 3 5B 4 16 by llama-moe

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  Arxiv:2310.06694   Arxiv:2406.16554   Autotrain compatible   Custom code   En   Llama moe   Moe   Pytorch   Region:us   Sharded

LLaMA MoE V1 3 5B 4 16 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
LLaMA MoE V1 3 5B 4 16 (llama-moe/LLaMA-MoE-v1-3_5B-4_16)

LLaMA MoE V1 3 5B 4 16 Parameters and Internals

Model Type 
text generation, MoE (Mixture-of-Experts)
Use Cases 
Areas:
Research, Deployment
Applications:
Not suitable as a chatbot
Additional Notes 
The model LLaMA-MoE does not perform optimally as a chatbot as it is not fine-tuned with instruction pairs.
Supported Languages 
en (English)
Training Details 
Data Sources:
SlimPajama, RedPajama
Data Volume:
200B tokens
Methodology:
Continual Pre-training, Mixture-of-Experts
Model Architecture:
Partitioning LLaMA FFNs into experts
Input Output 
Accepted Modalities:
text
LLM NameLLaMA MoE V1 3 5B 4 16
Repository ๐Ÿค—https://huggingface.co/llama-moe/LLaMA-MoE-v1-3_5B-4_16 
Model Size5b
Required VRAM13.5 GB
Updated2025-02-22
Maintainerllama-moe
Model Typellama_moe
Model Files  10.0 GB: 1-of-2   3.5 GB: 2-of-2
Supported Languagesen
Model ArchitectureLlamaMoEForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.31.0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16

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Rank the LLaMA MoE V1 3 5B 4 16 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 v20241227