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Bert Chinese L 12 H 768 A 12 by Tongjilibo

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  Endpoints compatible   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/Tongjilibo/bert-chinese_L-12_H-768_A-12 

Bert Chinese L 12 H 768 A 12 Benchmarks

LLME Score: 0.16835
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Bert Chinese L 12 H 768 A 12 (Tongjilibo/bert-chinese_L-12_H-768_A-12)

Bert Chinese L 12 H 768 A 12 Parameters and Internals

Model Type 
Text Embedding, Transformer
Use Cases 
Areas:
Research, Natural Language Processing
Applications:
Syntactic and semantic text analysis, Text embedding generation
Primary Use Cases:
Chinese text embedding for natural language understanding tasks
Additional Notes 
The BERT 'chinese_L-12_H-768_A-12' and 'bert-base-chinese' weights are reportedly the same.
Supported Languages 
Chinese (Proficient)
Training Details 
Data Sources:
Chinese datasets
Methodology:
Transformer architecture
Context Length:
512
Model Architecture:
12-layer, 768-hidden, 12-heads BERT architecture
Input Output 
Input Format:
Tokenized input sequences
Accepted Modalities:
text
Output Format:
Text embeddings
Performance Tips:
Use pre-trained models for enhanced language understanding
LLM NameBert Chinese L 12 H 768 A 12
Repository 🤗https://huggingface.co/Tongjilibo/bert-chinese_L-12_H-768_A-12 
Required VRAM0.4 GB
Updated2025-02-05
MaintainerTongjilibo
Model Files  0.4 GB
Model ArchitectureAutoModel
Licenseapache-2.0
Context Length512
Model Max Length512
Vocabulary Size21128

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Note: green Score (e.g. "73.2") means that the model is better than Tongjilibo/bert-chinese_L-12_H-768_A-12.

Rank the Bert Chinese L 12 H 768 A 12 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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