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EZO Common T2 2B Gemma 2 It by HODACHI

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EZO Common T2 2B Gemma 2 It is an open-source language model by HODACHI. Features: 2b LLM, VRAM: 5.2GB, Context: 8K, License: gemma, LLM Explorer Score: 0.15.

  Conversational   Endpoints compatible   Gemma2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/AXCXEPT/EZO-Common-T2-2B-gemma-2-it 

EZO Common T2 2B Gemma 2 It Benchmarks

LLME Score: 0.15267
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
EZO Common T2 2B Gemma 2 It (AXCXEPT/EZO-Common-T2-2B-gemma-2-it)
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EZO Common T2 2B Gemma 2 It Parameters and Internals

Model Type 
text generation, conversational
Use Cases 
Areas:
Global applications
Considerations:
This model is suitable for global use due to its diverse language training.
Additional Notes 
The model excels in Japanese language tasks but is designed for diverse global needs.
Supported Languages 
Japanese (high proficiency), Other languages (varied proficiency)
Training Details 
Data Sources:
https://huggingface.co/datasets/legacy-datasets/wikipedia, https://huggingface.co/datasets/HuggingFaceFW/fineweb
Data Volume:
Japanese Wikipedia and FineWeb data
Methodology:
Plain instruction tuning
Training Time:
4 hours
Hardware Used:
A100 x 8
Model Architecture:
Enhanced Gemma-2-2B-it with multiple tuning techniques
LLM NameEZO Common T2 2B Gemma 2 It
Repository 🤗https://huggingface.co/AXCXEPT/EZO-Common-T2-2B-gemma-2-it 
Model Size2b
Required VRAM5.2 GB
Updated2026-04-17
MaintainerHODACHI
Model Typegemma2
Model Files  5.0 GB: 1-of-2   0.2 GB: 2-of-2
Model ArchitectureGemma2ForCausalLM
Licensegemma
Context Length8192
Model Max Length8192
Transformers Version4.43.3
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than AXCXEPT/EZO-Common-T2-2B-gemma-2-it.

Rank the EZO Common T2 2B Gemma 2 It 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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