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MiniCPM MoE 8x2B by openbmb

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  Autotrain compatible   Conversational   Custom code   Moe   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/openbmb/MiniCPM-MoE-8x2B 

MiniCPM MoE 8x2B Benchmarks

LLME Score: 0.21194
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MiniCPM MoE 8x2B (openbmb/MiniCPM-MoE-8x2B)

MiniCPM MoE 8x2B Parameters and Internals

Model Type 
decoder-only, transformer-based, generative, Mixture-of-Experts (MoE)
Additional Notes 
- Instruction tuned but without other RLHF methods.\n- Model weights are in bfloat16 precision.\n- For more inference throughput, use vLLM (>=0.4.1) which is compatible with this model.
LLM NameMiniCPM MoE 8x2B
Repository 🤗https://huggingface.co/openbmb/MiniCPM-MoE-8x2B 
Model Size2b
Required VRAM27.7 GB
Updated2024-12-21
Maintaineropenbmb
Model Files  27.7 GB
Model ArchitectureMiniCPMForCausalLM
Context Length4096
Model Max Length4096
Transformers Version4.36.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size122753
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than openbmb/MiniCPM-MoE-8x2B.

Rank the MiniCPM MoE 8x2B 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  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217
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