MiniCPM 2B DPO Fp16 by openbmb

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MiniCPM 2B DPO Fp16 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 DPO Fp16 (openbmb/MiniCPM-2B-dpo-fp16)

MiniCPM 2B DPO Fp16 Parameters and Internals

Model Type 
Language Model
Use Cases 
Areas:
academic research, limited commercial applications
Primary Use Cases:
language modeling, multi-modal applications
Limitations:
Potential hallucinatory issues, Influence by prompt words, Knowledge memory less accurate
Considerations:
Further improvements to be made.
Additional Notes 
Model experiments ongoing to enhance features and reduce hallucinations.
Supported Languages 
zh (Chinese), en (English)
Training Details 
Data Sources:
ShareGPT open-source corpus
Methodology:
SFT, DPO
Hardware Used:
1080, 2080, 3090, 4090 GPUs
Responsible Ai Considerations 
Fairness:
Ensure model outputs do not represent developers' viewpoints.
Accountability:
Users are responsible for evaluating and verifying the model output.
Input Output 
Input Format:
Prompt-based input
Accepted Modalities:
text, multi-modal
Output Format:
Text
Performance Tips:
Use 'vLLM' for better generation quality.
LLM NameMiniCPM 2B DPO Fp16
Repository ๐Ÿค—https://huggingface.co/openbmb/MiniCPM-2B-dpo-fp16 
Base Model(s)  MiniCPM 2B DPO Fp32   openbmb/MiniCPM-2B-dpo-fp32
Model Size2b
Required VRAM5.5 GB
Updated2025-02-05
Maintaineropenbmb
Model Files  5.5 GB
Supported Languagesen zh
Quantization Typefp16
Model ArchitectureMiniCPMForCausalLM
Context Length4096
Model Max Length4096
Transformers Version4.36.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size122753
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than openbmb/MiniCPM-2B-dpo-fp16.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Data Analysis and Insight Generation  
Text Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227