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Gemma 1.1 2B It GPTQ by TechxGenus

 »  All LLMs  »  TechxGenus  »  Gemma 1.1 2B It GPTQ   URL Share it on

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  Arxiv:1705.03551   Arxiv:1804.06876   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:2107.03374   Arxiv:2108.07732   Arxiv:2110.08193   Arxiv:2110.14168   Arxiv:2206.04615   Arxiv:2304.06364   Arxiv:2312.11805   4-bit   Conversational   Endpoints compatible   Gemma   Gptq   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TechxGenus/gemma-1.1-2b-it-GPTQ 

Gemma 1.1 2B It GPTQ Benchmarks

LLME Score: 0.19191
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma 1.1 2B It GPTQ (TechxGenus/gemma-1.1-2b-it-GPTQ)
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Gemma 1.1 2B It GPTQ Parameters and Internals

Model Type 
text-to-text, decoder-only, language model
Use Cases 
Areas:
Research, Commercial applications
Applications:
Text Generation, Chatbots and Conversational AI, Text Summarization
Primary Use Cases:
Content Creation and Communication, Research and Education
Limitations:
Biases in training data, Context complexity, Language Ambiguity, Factual inaccuracies
Considerations:
Adherence to privacy regulations, using caution in deployments.
Additional Notes 
Supports various precisions including bfloat16, float16, and float32 for diverse hardware compatibility.
Supported Languages 
English (Fluent)
Training Details 
Data Sources:
Web Documents, Code, Mathematics
Data Volume:
6 trillion tokens
Methodology:
RLHF methods
Hardware Used:
TPUv5e
Model Architecture:
Open large language model, text-to-text, decoder-only
Safety Evaluation 
Methodologies:
Red-teaming, Human evaluation, Automated evaluation
Findings:
Results within acceptable thresholds for child safety, content safety, representational harms, Well known safety benchmarks results provided
Risk Categories:
Text-to-Text Content Safety, Text-to-Text Representational Harms, Large-scale harm
Ethical Considerations:
Memorization, large-scale harms
Responsible Ai Considerations 
Fairness:
Careful scrutiny, input data pre-processing and posterior evaluations done.
Transparency:
This model card contains detailed architecture, capabilities, and evaluation processes.
Accountability:
Google takes responsibility for releasing the Gemma model.
Mitigation Strategies:
Filtering sensitive data, providing guidelines for responsible usage, continuous monitoring and de-biasing.
Input Output 
Input Format:
Text string
Accepted Modalities:
text
Output Format:
English-language text
Performance Tips:
Utilize appropriate hardware and precision settings for optimal performance.
Release Notes 
Version:
1.1
Notes:
Gemma 1.1 was trained using a novel RLHF method, addressing aspects like response quality, instruction following, etc. Fixed multi-turn conversation bug, model improvements over previous releases.
LLM NameGemma 1.1 2B It GPTQ
Repository 🤗https://huggingface.co/TechxGenus/gemma-1.1-2b-it-GPTQ 
Base Model(s)  google/gemma-1.1-2b-it   google/gemma-1.1-2b-it
Model Size2b
Required VRAM3.1 GB
Updated2025-12-09
MaintainerTechxGenus
Model Typegemma
Model Files  3.1 GB
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureGemmaForCausalLM
Licensegemma
Context Length8192
Model Max Length8192
Transformers Version4.39.3
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typefloat16

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Rank the Gemma 1.1 2B It GPTQ 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 v20241124
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