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Open Calm 7B by cyberagent

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  Autotrain compatible   Dataset:cc100   Dataset:mc4   Dataset:wikipedia   Gpt neox   Ja   Japanese   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/cyberagent/open-calm-7b 

Open Calm 7B Benchmarks

ARC: 20.48 vs 96.7 (so35)-78.8%
HellaSwag: 30.65 vs 95.3 (gpt4)-67.8%
MMLU: 25.22 vs 88.3 (so35)-71.4%
TruthfulQA: 44.15 vs 59 (gpt4)-25.2%
WinoGrande: 48.54 vs 87.5 (gpt4)-44.5%
GSM8K: 0.23 vs 96.4 (so35)-99.8%
LLME Score: 0.19795
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Open Calm 7B (cyberagent/open-calm-7b)
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Open Calm 7B Parameters and Internals

Model Type 
Transformer-based Language Model, causal-lm
Additional Notes 
This model is a fine-tuned version of OpenCALM-XX developed by CyberAgent, Inc. The model uses GPT-NeoX, a large-scale autoregressive language modeling library in PyTorch.
Supported Languages 
ja (Proficient)
Training Details 
Data Sources:
Wikipedia (ja), Common Crawl (ja)
Model Architecture:
Decoder-only
LLM NameOpen Calm 7B
Repository 🤗https://huggingface.co/cyberagent/open-calm-7b 
Model Size7b
Required VRAM13.9 GB
Updated2025-09-16
Maintainercyberagent
Model Typegpt_neox
Model Files  9.9 GB: 1-of-2   4.0 GB: 2-of-2
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 Size52224
Torch Data Typefloat16

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Rank the Open Calm 7B 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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Release v20241124
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