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Google Gemma 2 27B It by SillyTilly

 »  All LLMs  »  SillyTilly  »  Google Gemma 2 27B It   URL Share it on

  120   
  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   Autotrain compatible   Conversational   Endpoints compatible   Gemma2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/SillyTilly/google-gemma-2-27b-it 

Google Gemma 2 27B It Benchmarks

LLME Score: 0.21175
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Google Gemma 2 27B It (SillyTilly/google-gemma-2-27b-it)

Google Gemma 2 27B It Parameters and Internals

Model Type 
text-to-text, decoder-only, large language model
Use Cases 
Areas:
Research, Commercial applications
Applications:
text generation, chatbots, text summarization, language learning tools, knowledge exploration
Primary Use Cases:
Content Creation and Communication, Research and Education
Limitations:
Training Data, Context and Task Complexity, Language Ambiguity and Nuance, Factual Accuracy, Common Sense
Supported Languages 
English (Full support)
Training Details 
Data Sources:
Web Documents, Code, Mathematics
Data Volume:
13 trillion tokens (27B model); 8 trillion tokens (9B model)
Methodology:
Built using the same research and technology as Gemini models
Hardware Used:
TPUv5p
Safety Evaluation 
Methodologies:
structured evaluations, internal red-teaming
Risk Categories:
child safety, content safety, representational harms, memorization, large-scale harms
Responsible Ai Considerations 
Fairness:
These models underwent careful scrutiny, input data pre-processing described and posterior evaluations reported in this card.
Transparency:
This model card summarizes details on the models' architecture, capabilities, limitations, and evaluation processes.
Mitigation Strategies:
Continuous monitoring and exploration of de-biasing techniques; Guidelines for content safety provided
Input Output 
Input Format:
Text string (e.g., question, prompt, document to be summarized)
Accepted Modalities:
text
Output Format:
Generated English-language text
LLM NameGoogle Gemma 2 27B It
Repository 🤗https://huggingface.co/SillyTilly/google-gemma-2-27b-it 
Model Size27b
Required VRAM54.7 GB
Updated2025-01-03
MaintainerSillyTilly
Model Typegemma2
Model Files  4.7 GB: 1-of-12   4.9 GB: 2-of-12   4.9 GB: 3-of-12   5.0 GB: 4-of-12   4.9 GB: 5-of-12   4.9 GB: 6-of-12   5.0 GB: 7-of-12   4.9 GB: 8-of-12   4.9 GB: 9-of-12   5.0 GB: 10-of-12   4.9 GB: 11-of-12   0.7 GB: 12-of-12
Model ArchitectureGemma2ForCausalLM
Licensegemma
Context Length8192
Model Max Length8192
Transformers Version4.42.0.dev0
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 SillyTilly/google-gemma-2-27b-it.

Rank the Google Gemma 2 27B 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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Release v20241227
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