MiniCPM S 1B Sft by openbmb

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  Arxiv:2310.04564   Arxiv:2312.12456   Arxiv:2402.03804   Arxiv:2402.13516   Arxiv:2404.06395   Autotrain compatible   Conversational   Custom code   En   Minicpm   Modelbest   Pytorch   Region:us   Safetensors   Thunlp   Zh

MiniCPM S 1B Sft Benchmarks

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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MiniCPM S 1B Sft Parameters and Internals

Model Type 
text generation, multimodal
Supported Languages 
en (high), zh (high)
Training Details 
Data Sources:
Mixed Dataset
Data Volume:
473.02 billion tokens
Methodology:
ProSparse
Training Time:
101,000 steps
Model Architecture:
Swish-activated LLaMA2 to ReLU-activated
Input Output 
Input Format:
<็”จๆˆท>{prompt}, Ensure bos token `~~` in inputs
Accepted Modalities:
text
Output Format:
text response
Performance Tips:
Use standard chat prompts
Release Notes 
Version:
1.0
Date:
2024-04-15
Notes:
Initial release with ProSparse approach and high sparsity.
LLM NameMiniCPM S 1B Sft
Repository ๐Ÿค—https://huggingface.co/openbmb/MiniCPM-S-1B-sft 
Model Size1b
Required VRAM2.7 GB
Updated2025-06-09
Maintaineropenbmb
Model Files  2.7 GB   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
MiniCPM S 1B Sft (openbmb/MiniCPM-S-1B-sft)

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Rank the MiniCPM S 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