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ProSparse MiniCPM 1B Sft by SparseLLM

 »  All LLMs  »  SparseLLM  »  ProSparse MiniCPM 1B Sft   URL Share it on

  20   
  Arxiv:2310.04564   Arxiv:2312.12456   Arxiv:2402.03804   Arxiv:2402.13516   Arxiv:2404.06395   Autotrain compatible   Custom code   En   Minicpm   Modelbest   Pytorch   Region:us   Thunlp   Zh
Model Card on HF 🤗: https://huggingface.co/SparseLLM/ProSparse-MiniCPM-1B-sft 

ProSparse MiniCPM 1B Sft Benchmarks

LLME Score: 0.17206
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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ProSparse MiniCPM 1B Sft Parameters and Internals

Model Type 
language model, sparsity-enhanced
Use Cases 
Areas:
research, commercial applications
Applications:
text generation, code generation, reading comprehension
Primary Use Cases:
Inference speed enhancement due to sparsity
Limitations:
Potential inaccuracies with activation predictor, Evaluation issues with LM-Eval
Considerations:
Use UltraEval for evaluation; handle limitations in inference accuracy carefully.
Supported Languages 
en (proficient), zh (proficient)
Training Details 
Data Sources:
ProSparse training methodology
Data Volume:
473.02 billion tokens
Methodology:
Activation Function Substitution, Progressive Sparsity Regularization, Activation Threshold Shifting
Model Architecture:
Modified version of MiniCPM using ProSparse method with ReLU activation substitution
Input Output 
Input Format:
Tokenized text
Accepted Modalities:
text
Output Format:
Tokenized text
Performance Tips:
Utilize PowerInfer for acceleration.
LLM NameProSparse MiniCPM 1B Sft
Repository 🤗https://huggingface.co/SparseLLM/ProSparse-MiniCPM-1B-sft 
Model Size1b
Required VRAM2.7 GB
Updated2025-06-09
MaintainerSparseLLM
Model Files  2.7 GB
Supported Languagesen zh
Model ArchitectureMiniCPMForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.36.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size73440
Torch Data Typebfloat16
ProSparse MiniCPM 1B Sft (SparseLLM/ProSparse-MiniCPM-1B-sft)

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Note: green Score (e.g. "73.2") means that the model is better than SparseLLM/ProSparse-MiniCPM-1B-sft.

Rank the ProSparse MiniCPM 1B Sft 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 v20241124
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