MiniCPM 2B History by openbmb

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  Autotrain compatible   Conversational   Custom code   En   Minicpm   Modelbest   Region:us   Thunlp   Zh

MiniCPM 2B History Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MiniCPM 2B History (openbmb/MiniCPM-2B-history)

MiniCPM 2B History Parameters and Internals

Model Type 
language model, multimodal model
Use Cases 
Areas:
academic research, commercial applications
Applications:
multimodal tasks, language generation
Primary Use Cases:
deployable on smartphones
Limitations:
Hallucinatory issues due to model size, influenced by prompt words, inaccurate knowledge memory.
Considerations:
Model outputs need user evaluation and verification.
Additional Notes 
MiniCPM can stream inference outputs faster than human verbal speed.
Supported Languages 
en (high), zh (high)
Training Details 
Data Sources:
ShareGPT open-source corpus
Methodology:
Standard training with SFT and DPO
Safety Evaluation 
Risk Categories:
hallucination
Responsible Ai Considerations 
Transparency:
Model outputs may be influenced by prompts due to its size.
Mitigation Strategies:
Combination with RAG method planned to enhance model's knowledge memory.
Input Output 
Input Format:
text prompts
Accepted Modalities:
text, multimodal inputs
Output Format:
language outputs including text and multimodal responses
Performance Tips:
Benchmarking using vLLM is recommended for optimal quality.
LLM NameMiniCPM 2B History
Repository ๐Ÿค—https://huggingface.co/openbmb/MiniCPM-2B-history 
Model Size2b
Updated2025-01-20
Maintaineropenbmb
Supported Languagesen zh
Model ArchitectureMiniCPMForCausalLM
Context Length4096
Model Max Length4096
Transformers Version4.36.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size122753
Torch Data Typebfloat16

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...iniCPM 2B DPO Fp32 Safetensors4K / 10.9 GB81
...iniCPM 2B DPO Bf16 Safetensors4K / 5.5 GB71
...iniCPM 2B Sft Fp32 Safetensors4K / 10.9 GB71
...iniCPM 2B Sft Fp32 Safetensors4K / 10.9 GB61
Note: green Score (e.g. "73.2") means that the model is better than openbmb/MiniCPM-2B-history.

Rank the MiniCPM 2B History 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