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Coref Bert Large by nielsr

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  Arxiv:2004.06870   Dataset:docred   Dataset:fever   Dataset:gap   Dataset:nyu-mll/glue   Dataset:quoref   Dataset:wikipedia   Dataset:winogender   Dataset:winograd wsc   En   Endpoints compatible   Exbert   Pytorch   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/nielsr/coref-bert-large 

Coref Bert Large Benchmarks

LLME Score: 0.001
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Coref Bert Large (nielsr/coref-bert-large)
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Coref Bert Large Parameters and Internals

Model Type 
Masked Language Modeling (MLM), Mention Reference Prediction (MRP)
Additional Notes 
The CorefBERT model is pretrained in a self-supervised fashion allowing it to be trained on large publicly available datasets without labeled data.
Supported Languages 
English (Proficient)
Training Details 
Data Sources:
wikipedia, quoref, docred, fever, gap, winograd_wsc, winogender, nyu-mll/glue
Model Architecture:
Transformers
LLM NameCoref Bert Large
Repository 🤗https://huggingface.co/nielsr/coref-bert-large 
Model Size334.7m
Required VRAM1.3 GB
Updated2025-09-23
Maintainernielsr
Model Files  1.3 GB   1.3 GB
Supported Languagesen
Model ArchitectureAutoModel
Licenseapache-2.0
Context Length512
Model Max Length512
Vocabulary Size28996

Rank the Coref Bert Large 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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