LLM EXPLORER
 LLM Explorer: A Curated Large Language Model Directory and Analytics
Dark Theme
  LLM  List    LLM Hosting    LLM Leaderboards    Blog    Newsfeed    Advertise

Gemma 7B by google

 »  All LLMs  »  google  »  Gemma 7B   URL Share it on

  259992   
  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:2305.14314   Arxiv:2312.11805   Autotrain compatible   Endpoints compatible   Gemma   Gguf   Quantized   Region:us   Safetensors   Sharded   Tensorflow

Gemma 7B Benchmarks

MMLU Pro: 7.72
GPQA: 4.59
MUSR: 12.53
BBH: 11.88
IFEval: 38.68 vs 88 (so35)-56%
ARC: 61.09 vs 96.7 (so35)-36.8%
HellaSwag: 82.2 vs 95.3 (gpt4)-13.7%
MMLU: 64.56 vs 88.3 (so35)-26.9%
TruthfulQA: 44.79 vs 59 (gpt4)-24.1%
WinoGrande: 79.01 vs 87.5 (gpt4)-9.7%
GSM8K: 50.87 vs 96.4 (so35)-47.2%
MATH Lvl 5: 1.81
LLME Score: 0.46313
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Gemma 7B Parameters and Internals

Model Type 
text-to-text, decoder-only, large language models
Use Cases 
Areas:
Content Creation and Communication, Research and Education
Applications:
Text Generation, Chatbots and Conversational AI, Text Summarization, Natural Language Processing Research, Language Learning Tools, Knowledge Exploration
Primary Use Cases:
Question answering, Summarization, Reasoning
Limitations:
Biases from training data, Complex task handling limitations, Figurative language and nuances issues, Factual inaccuracies
Considerations:
Continuous monitoring, content safety guidelines, and education around privacy.
Supported Languages 
English (full)
Training Details 
Data Sources:
Web Documents, Code, Mathematics
Data Volume:
6 trillion tokens
Context Length:
8192
Hardware Used:
TPUv5e
Model Architecture:
text-to-text, decoder-only large language model
Safety Evaluation 
Methodologies:
structured evaluations, internal red-teaming
Findings:
acceptable thresholds for internal policies
Risk Categories:
Text-to-Text Content Safety, Text-to-Text Representational Harms, Memorization, Large-scale harm
Ethical Considerations:
Bias and Fairness, Misinformation, Transparency
Responsible Ai Considerations 
Fairness:
The model underwent input data pre-processing and evaluations to assess socio-cultural biases.
Transparency:
Summarizes details on architecture, capabilities, and limitations.
Accountability:
Open model development aims to share innovation with developers and researchers.
Mitigation Strategies:
De-biasing techniques, content safety mechanisms, and end-user education.
Input Output 
Input Format:
Text string
Accepted Modalities:
text
Output Format:
Generated English-language text
LLM NameGemma 7B
Repository 🤗https://huggingface.co/google/gemma-7b 
Base Model(s)  Gemma Ei Oc Structured Train   Holmeister/Gemma_ei_oc_structured_train
Model Size7b
Required VRAM17.1 GB
Updated2024-11-21
Maintainergoogle
Model Typegemma
Model Files  34.2 GB   5.0 GB: 1-of-4   5.0 GB: 2-of-4   5.0 GB: 3-of-4   2.1 GB: 4-of-4
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureGemmaForCausalLM
Licensegemma
Context Length8192
Model Max Length8192
Transformers Version4.38.0.dev0
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typebfloat16
Gemma 7B (google/gemma-7b)

Quantized Models of the Gemma 7B

Model
Likes
Downloads
VRAM
Gemma 7B It113967631817 GB
Train060349 GB
CNCF0175 GB
Gemma 7B GGUF104283 GB

Best Alternatives to Gemma 7B

Best Alternatives
Context / RAM
Downloads
Likes
Gemma 7B It8K / 17.1 GB6763181139
Gemma 1.1 7B It GGUF8K / 5.3 GB321
Train068K / 9.1 GB340
Llama2 Kazakh 7B GGUF8K / 4.1 GB80
Gemma 7B8K / 17.1 GB60
Gemma 7B Translator 0.48K / 17.1 GB210
Gemma 7B Translator 0.38K / 17.1 GB60
Gemma7B Konosuba8K / 17.1 GB70
Gemma 7B It GGUF8K / 5.3 GB291
Gemma 7B It GGUF8K / 3.1 GB23711
Note: green Score (e.g. "73.2") means that the model is better than google/gemma-7b.

Rank the Gemma 7B 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  

What open-source LLMs or SLMs are you in search of? 38149 in total.

Email us: info@extractum.io. Our Privacy Policy  | Terms and Conditions  | Suggest an improvement.
Our Social Media →  
Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241110
  Support LLM Explorer