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Fanar 1 9B Instruct by QCRI

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  Arxiv:2501.13944   Ar   Autotrain compatible Base model:finetune:qcri/fanar...   Base model:qcri/fanar-1-9b   Conversational   En   Endpoints compatible   Gemma2   Instruct   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/QCRI/Fanar-1-9B-Instruct 

Fanar 1 9B Instruct Benchmarks

LLME Score: 0.31052
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Fanar 1 9B Instruct (QCRI/Fanar-1-9B-Instruct)
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Fanar 1 9B Instruct Parameters and Internals

LLM NameFanar 1 9B Instruct
Repository 🤗https://huggingface.co/QCRI/Fanar-1-9B-Instruct 
Base Model(s)  Fanar 1 9B   QCRI/Fanar-1-9B
Model Size9b
Required VRAM17.7 GB
Updated2025-08-10
MaintainerQCRI
Model Typegemma2
Instruction-BasedYes
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   5.0 GB: 3-of-4   2.7 GB: 4-of-4
Supported Languagesar en
Model ArchitectureGemma2ForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.47.1
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size128256
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than QCRI/Fanar-1-9B-Instruct.

Rank the Fanar 1 9B Instruct 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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