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Gemma Ko 2B by beomi

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Gemma Ko 2B is an open-source language model by beomi. Features: 2b LLM, VRAM: 5.1GB, Context: 8K, License: other, LLM Explorer Score: 0.13.

  En   Endpoints compatible   Gemma   Ko   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/beomi/gemma-ko-2b 

Gemma Ko 2B Benchmarks

LLME Score: 0.12796
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma Ko 2B (beomi/gemma-ko-2b)
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Gemma Ko 2B Parameters and Internals

Model Type 
text generation
Additional Notes 
These models can be used for various applications such as content creation, research, NLP techniques, etc. Known limitations include biases or gaps in training data, context and task complexity, language ambiguity, factual accuracy, and common sense.
Supported Languages 
Korean (fluent), English (fluent)
Input Output 
Input Format:
Text string, such as a question, a prompt, or a document to be summarized.
Output Format:
Generated Korean/English-language text in response to the input.
Performance Tips:
Longer context generally leads to better outputs, up to a certain point.
Release Notes 
Version:
2B
Date:
2024.03.26
Notes:
First release of Gemma-Ko 2B model
LLM NameGemma Ko 2B
Repository 🤗https://huggingface.co/beomi/gemma-ko-2b 
Model Size2b
Required VRAM5.1 GB
Updated2026-05-06
Maintainerbeomi
Model Typegemma
Model Files  5.0 GB: 1-of-2   0.1 GB: 2-of-2
Supported Languagesko en
Model ArchitectureGemmaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.38.2
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 beomi/gemma-ko-2b.

Rank the Gemma Ko 2B 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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