Open Calm Small by cyberagent

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  Autotrain compatible   Dataset:cc100   Dataset:mc4   Dataset:wikipedia   Gpt neox   Ja   Japanese   Pytorch   Region:us

Open Calm Small Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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Open Calm Small Parameters and Internals

Model Type 
Transformer-based Language Model, Causal Language Model
Additional Notes 
OpenCALM is a suite of decoder-only language models pre-trained on Japanese datasets.
Supported Languages 
Japanese (Primary)
Training Details 
Data Sources:
Wikipedia (ja), Common Crawl (ja)
Methodology:
Fine-tuning
Model Architecture:
Decoder-only
Input Output 
Input Format:
Tokenized text input
Accepted Modalities:
text
Output Format:
Generated text output
LLM NameOpen Calm Small
Repository ๐Ÿค—https://huggingface.co/cyberagent/open-calm-small 
Required VRAM0.4 GB
Updated2025-06-09
Maintainercyberagent
Model Typegpt_neox
Model Files  0.4 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
Open Calm Small (cyberagent/open-calm-small)

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Note: green Score (e.g. "73.2") means that the model is better than cyberagent/open-calm-small.

Rank the Open Calm Small 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