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Gemma 1.1 7B It GPTQ by TechxGenus

 »  All LLMs  »  TechxGenus  »  Gemma 1.1 7B It GPTQ   URL Share it on

  7   
  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   Autotrain compatible   Conversational   Endpoints compatible   Gemma   Gptq   Quantized   Region:us   Safetensors

Gemma 1.1 7B It GPTQ Benchmarks

ARC: 59.98 vs 96.7 (so35)-38%
HellaSwag: 76.21 vs 95.3 (gpt4)-20%
MMLU: 60.39 vs 88.3 (so35)-31.6%
TruthfulQA: 50.4 vs 59 (gpt4)-14.6%
WinoGrande: 69.93 vs 87.5 (gpt4)-20.1%
GSM8K: 41.77 vs 96.4 (so35)-56.7%
LLME Score: 0.21337
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 7B It GPTQ Parameters and Internals

Model Type 
text generation, decoder-only, large language model
Use Cases 
Areas:
Content Creation, Communication, Research, Education
Applications:
Text Generation, Chatbots and Conversational AI, Text Summarization, NLP Research, Language Learning Tools
Primary Use Cases:
Content creation, research, and education.
Limitations:
Bias and Fairness, Misinformation and Misuse, Transparency and Accountability, Privacy violations
Considerations:
Perform continuous monitoring and implement appropriate content safety safeguards.
Supported Languages 
English (High)
Training Details 
Data Sources:
Web Documents, Code, Mathematics
Data Volume:
6 trillion tokens
Methodology:
RLHF
Hardware Used:
TPUv5e
Model Architecture:
N/A
Safety Evaluation 
Methodologies:
Text-to-Text Content Safety, Text-to-Text Representational Harms Benchmark, Memorization
Findings:
Acceptable thresholds for categories like child safety, content safety, representational harms, memorization, large-scale harms
Risk Categories:
child safety, content safety, representational harms, memorization, large-scale harms
Ethical Considerations:
Within acceptable thresholds for internal policies
Responsible Ai Considerations 
Fairness:
Careful scrutiny, input data pre-processing and posterior evaluations.
Transparency:
This model card summarizes model details.
Accountability:
N/A
Mitigation Strategies:
Encouraged monitoring and exploration of de-biasing techniques.
Input Output 
Input Format:
Text string such as a question, prompt, or document to be summarized.
Accepted Modalities:
text
Output Format:
Generated English-language text.
Release Notes 
Version:
1.1
Date:
N/A
Notes:
An update over the original instruction-tuned Gemma release, trained using a novel RLHF method with improvements in quality, coding capabilities, factuality, instruction following, and multi-turn conversation quality.
LLM NameGemma 1.1 7B It GPTQ
Repository 🤗https://huggingface.co/TechxGenus/gemma-1.1-7b-it-GPTQ 
Base Model(s)  unsloth/gemma-1.1-7b-it   unsloth/gemma-1.1-7b-it
Model Size7b
Required VRAM7.2 GB
Updated2024-11-23
MaintainerTechxGenus
Model Typegemma
Model Files  7.2 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
Gemma 1.1 7B It GPTQ (TechxGenus/gemma-1.1-7b-it-GPTQ)

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Note: green Score (e.g. "73.2") means that the model is better than TechxGenus/gemma-1.1-7b-it-GPTQ.

Rank the Gemma 1.1 7B 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 v20241110
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