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Open Calm Large by cyberagent

 »  All LLMs  »  cyberagent  »  Open Calm Large   URL Share it on

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  Autotrain compatible   Dataset:cc100   Dataset:mc4   Dataset:wikipedia   Gpt neox   Ja   Japanese   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/cyberagent/open-calm-large 

Open Calm Large Benchmarks

ARC: 20.73 vs 96.7 (so35)-78.6%
HellaSwag: 29.56 vs 95.3 (gpt4)-69%
MMLU: 25.23 vs 88.3 (so35)-71.4%
TruthfulQA: 46.52 vs 59 (gpt4)-21.2%
WinoGrande: 51.14 vs 87.5 (gpt4)-41.6%
GSM8K: 0.08 vs 96.4 (so35)-99.9%
LLME Score: 0.15082
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Open Calm Large (cyberagent/open-calm-large)
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Open Calm Large Parameters and Internals

Model Type 
Transformer-based Language Model
Use Cases 
Areas:
Japanese Text Generation
Additional Notes 
The model is part of a suite of language models and is implemented using the GPT-NeoX library. The OpenCALM-Large model is specifically designed for Japanese language tasks.
Supported Languages 
Japanese (Full)
Training Details 
Data Sources:
Wikipedia (ja), Common Crawl (ja)
Model Architecture:
Decoder-only
LLM NameOpen Calm Large
Repository 🤗https://huggingface.co/cyberagent/open-calm-large 
Required VRAM1.8 GB
Updated2025-09-23
Maintainercyberagent
Model Typegpt_neox
Model Files  1.8 GB
Supported Languagesja
Model ArchitectureGPTNeoXForCausalLM
Licensecc-by-sa-4.0
Context Length2048
Model Max Length2048
Transformers Version4.27.0.dev0
Tokenizer ClassGPTNeoXTokenizer
Padding Token<|padding|>
Vocabulary Size52096
Torch Data Typefloat16

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Rank the Open Calm Large Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Release v20241124
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