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Gemma 2 2B Persian by PersianML

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Gemma 2 2B Persian is an open-source language model by PersianML. Features: 2b LLM, VRAM: 5.2GB, Context: 8K, License: mit, Quantized, LLM Explorer Score: 0.27.

Base model:google/gemma-2-2b-i... Base model:quantized:google/ge...   Conversational   Dataset:mshojaei77/persian sft   Endpoints compatible   Experimental   Fa   Finetuned   Gemma   Gemma2   Gguf   Persian   Q8   Qlora   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/PersianML/gemma-2-2b-persian 

Gemma 2 2B Persian Benchmarks

LLME Score: 0.27296
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma 2 2B Persian (PersianML/gemma-2-2b-persian)

Gemma 2 2B Persian Parameters and Internals

LLM NameGemma 2 2B Persian
Repository 🤗https://huggingface.co/PersianML/gemma-2-2b-persian 
Base Model(s)  Gemma 2 2B It   google/gemma-2-2b-it
Model Size2b
Required VRAM5.2 GB
Updated2026-07-23
MaintainerPersianML
Model Typegemma2
Model Files  2.8 GB   5.0 GB: 1-of-2   0.2 GB: 2-of-2
Supported Languagesfa
GGUF QuantizationYes
Quantization Typeq8|gguf
Model ArchitectureGemma2ForCausalLM
Licensemit
Context Length8192
Model Max Length8192
Transformers Version4.49.0
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typefloat16

Best Alternatives to Gemma 2 2B Persian

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Gemma 2 2B Fa V28K / 5.3 GB374
Gemma 2 2B Fa8K / 5.2 GB494
Gemma 2 It GGUF8K / 1.2 GB172428
Gemma 2 2B It Bnb 4bit8K / 2.2 GB3681820
Gemma 2 2B Id Instruct8K / 5.2 GB750
Gemma 2 2B Id8K / 5.2 GB570
Gemma 2 2B Id Inst8K / 5.2 GB140
Athena Gemma 2 2B It Philos8K / 5.2 GB200
Arnab Ft Gemma2 From Vm St V18K / 5.2 GB70
Gemma 2 2B Bnb 4bit8K / 2.2 GB712212

Rank the Gemma 2 2B Persian 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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