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Gemma 2B by 4bit

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

  117   
  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:2107.03374   Arxiv:2108.07732   Arxiv:2109.07958   Arxiv:2110.08193   Arxiv:2110.14168   Arxiv:2203.09509   Arxiv:2206.04615   Arxiv:2304.06364   Arxiv:2312.11805   Autotrain compatible   Endpoints compatible   Gemma   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/4bit/gemma-2b 

Gemma 2B Benchmarks

LLME Score: 0.19868
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma 2B (4bit/gemma-2b)

Gemma 2B Parameters and Internals

Model Type 
text generation, decoder-only large language model
Use Cases 
Areas:
Content Creation and Communication, Research and Education
Applications:
Text Generation, Chatbots and Conversational AI, Text Summarization, NLP Research, Language Learning Tools, Knowledge Exploration
Primary Use Cases:
Summarization, Question Answering, Reasoning
Limitations:
Biases in training data, influence of context length, factual inaccuracies, struggles with nuance and open-ended tasks
Considerations:
Developers recommended to perform continuous evaluation, employ de-biasing techniques, and include safety measures for applications.
Additional Notes 
At release, provides implementation designed for Responsible AI development compared to similarly sized models in the ecosystem.
Supported Languages 
English (proficient)
Training Details 
Data Sources:
Web Documents, Code, Mathematics
Data Volume:
6 trillion tokens
Hardware Used:
TPUv5e
Model Architecture:
decoder-only
Safety Evaluation 
Risk Categories:
text-to-text content safety, text-to-text representational harms, memorization, large-scale harm
Responsible Ai Considerations 
Fairness:
Models underwent careful scrutiny and input data pre-processing described in this card. Continuous monitoring and de-biasing techniques are encouraged.
Transparency:
This model card and technical documentation details the model architecture, capabilities, evaluations.
Accountability:
Developers are encouraged to follow guidelines for responsible use and adhere to specific product policies and application use cases.
Mitigation Strategies:
Filtering harmful content and PII, transparency in documentation, setting guidelines for responsible usage and development.
Input Output 
Input Format:
Text string (question, prompt, document)
Accepted Modalities:
text
Output Format:
Generated English-language text
LLM NameGemma 2B
Repository 🤗https://huggingface.co/4bit/gemma-2b 
Model Size2b
Required VRAM5.1 GB
Updated2025-02-22
Maintainer4bit
Model Typegemma
Model Files  5.0 GB: 1-of-2   0.1 GB: 2-of-2
Model ArchitectureGemmaForCausalLM
Context Length8192
Model Max Length8192
Transformers Version4.38.0.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 4bit/gemma-2b.

Rank the Gemma 2B Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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