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Recurrentgemma 9B It by google

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  9741   
  Arxiv:1705.03551   Arxiv:1804.06876   Arxiv:1804.09301   Arxiv:1809.02789   Arxiv:1811.00937   Arxiv:1904.09728   Arxiv:1905.07830   Arxiv:1905.10044   Arxiv:1907.10641   Arxiv:1911.01547   Arxiv:1911.11641   Arxiv:2009.03300   Arxiv:2009.11462   Arxiv:2101.11718   Arxiv:2103.03874   Arxiv:2107.03374   Arxiv:2108.07732   Arxiv:2109.07958   Arxiv:2110.08193   Arxiv:2110.14168   Arxiv:2203.09509   Arxiv:2206.04615   Arxiv:2304.06364   Arxiv:2402.19427   Autotrain compatible   Conversational   Endpoints compatible   Recurrent gemma   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/google/recurrentgemma-9b-it 

Recurrentgemma 9B It Benchmarks

MMLU Pro: 20.48
GPQA: 2.68
MUSR: 13.77
BBH: 21.62
IFEval: 50.1 vs 88 (so35)-43.1%
MATH Lvl 5: 6.72
LLME Score: 0.30898
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Recurrentgemma 9B It (google/recurrentgemma-9b-it)

Recurrentgemma 9B It Parameters and Internals

Model Type 
text generation, instruction-tuned
Use Cases 
Areas:
content creation, research
Applications:
text generation, chatbots, summarization
Primary Use Cases:
creative text creation, interactive language tools
Limitations:
LLMs reflect socio-cultural biases, may generate fake or harmful content, not knowledge bases, privacy concerns
Supported Languages 
English (primary)
Training Details 
Data Sources:
Same training data as Gemma model family
Hardware Used:
TPUv5e
Model Architecture:
novel recurrent architecture
Responsible Ai Considerations 
Mitigation Strategies:
Developers encouraged to monitor, apply debiasing techniques, and implement content safety measures.
Input Output 
Input Format:
Text string
Output Format:
Generated English-language text
LLM NameRecurrentgemma 9B It
Repository 🤗https://huggingface.co/google/recurrentgemma-9b-it 
Model Size9b
Required VRAM19.3 GB
Updated2025-02-05
Maintainergoogle
Model Typerecurrent_gemma
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   4.4 GB: 4-of-4
Model ArchitectureRecurrentGemmaForCausalLM
Licensegemma
Transformers Version4.42.0.dev0
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typebfloat16

Quantized Models of the Recurrentgemma 9B It

Model
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Downloads
VRAM
Recurrentgemma 9B It Bnb 4bit0106 GB

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Rank the Recurrentgemma 9B It 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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