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Gemma 2 27B It 4bit by rainjay

 »  All LLMs  »  rainjay  »  Gemma 2 27B It 4bit   URL Share it on

  44   
  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   4-bit   4bit   Autotrain compatible   Bitsandbytes   Conversational   Endpoints compatible   Gemma2   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/rainjay/gemma-2-27b-it-4bit 

Gemma 2 27B It 4bit Benchmarks

LLME Score: 0.20884
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma 2 27B It 4bit (rainjay/gemma-2-27b-it-4bit)

Gemma 2 27B It 4bit Parameters and Internals

Model Type 
text generation, decoder-only large language models
Use Cases 
Areas:
content creation, communication, research and education
Applications:
text generation, chatbots, text summarization, NLP research, language learning tools
Primary Use Cases:
creative text generation, interactive applications, research assistance
Limitations:
training data biases, context and task complexity, language ambiguity, factual accuracy, common sense reasoning
Considerations:
Guidelines for responsible use as per Responsible Generative AI Toolkit.
Supported Languages 
English (native)
Training Details 
Data Sources:
Web Documents, Code, Mathematics
Data Volume:
27B model: 13 trillion tokens
Methodology:
Text-to-text, instruction-tuned
Hardware Used:
TPUv5p
Model Architecture:
decoder-only
Safety Evaluation 
Methodologies:
structured evaluations, internal red-teaming
Findings:
acceptable thresholds for internal policies
Risk Categories:
child safety, content safety, representational harms, memorization, large-scale harms
Ethical Considerations:
This model card summarizes details on the models' architecture, limitations, and evaluation processes.
Responsible Ai Considerations 
Fairness:
Careful scrutiny, input data pre-processing described and posterior evaluations reported.
Transparency:
This model card summarizes details on the models' architecture, capabilities, limitations, and evaluation processes.
Accountability:
Exploration of de-biasing techniques encouraged.
Mitigation Strategies:
Continuous monitoring encouraged.
Input Output 
Input Format:
Text string
Accepted Modalities:
text
Output Format:
Generated English-language text
LLM NameGemma 2 27B It 4bit
Repository 🤗https://huggingface.co/rainjay/gemma-2-27b-it-4bit 
Model Size27b
Required VRAM15.8 GB
Updated2025-01-02
Maintainerrainjay
Model Typegemma2
Model Files  6.0 GB: 1-of-3   5.9 GB: 2-of-3   3.9 GB: 3-of-3
Quantization Type4bit
Model ArchitectureGemma2ForCausalLM
Licensegemma
Context Length8192
Model Max Length8192
Transformers Version4.42.3
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 rainjay/gemma-2-27b-it-4bit.

Rank the Gemma 2 27B It 4bit 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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