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 It by google

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

  331554   
  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 Base model:finetune:google/gem...   Base model:google/gemma-7b   Conversational   Endpoints compatible   Gemma   Gguf   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/google/gemma-7b-it 

Gemma 7B It Benchmarks

LMSys ELO: 1037 vs 1272 (so35)-18.5%
MMLU Pro: 7.72
GPQA: 4.59
MUSR: 12.53
BBH: 11.88
IFEval: 38.68 vs 88 (so35)-56%
ARC: 51.45 vs 96.7 (so35)-46.8%
HellaSwag: 71.96 vs 95.3 (gpt4)-24.5%
MMLU: 53.52 vs 88.3 (so35)-39.4%
TruthfulQA: 47.29 vs 59 (gpt4)-19.8%
WinoGrande: 67.96 vs 87.5 (gpt4)-22.3%
GSM8K: 29.19 vs 96.4 (so35)-69.7%
MATH Lvl 5: 1.81
LLME Score: 0.5029
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma 7B It (google/gemma-7b-it)

Gemma 7B It Parameters and Internals

Model Type 
Text-to-text, Decoder-only large language models
Use Cases 
Areas:
Content Creation, Research, Education
Applications:
Text Generation, Chatbots, Text Summarization
Limitations:
Training data limitations, Context and task complexity, Language ambiguity, Factual accuracy issues
Considerations:
Guidelines provided for responsible use.
Supported Languages 
English (fluent)
Training Details 
Data Sources:
Web Documents, Code, Mathematics
Data Volume:
6 trillion tokens
Hardware Used:
TPUv5e
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:
Responsible Ai Considerations 
Fairness:
Scrutiny and data pre-processing done to mitigate biases.
Transparency:
Model card provides details on architecture, capabilities, and processes.
Accountability:
Google as the developer has oversight on model deployments.
Mitigation Strategies:
Developers are encouraged to follow guidelines for responsible use.
Input Output 
Input Format:
Text string (e.g., prompt or question)
Output Format:
Generated English-language text
LLM NameGemma 7B It
Repository 🤗https://huggingface.co/google/gemma-7b-it 
Base Model(s)  Gemma 7B   google/gemma-7b
Model Size7b
Required VRAM17.1 GB
Updated2024-12-21
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

Quantized Models of the Gemma 7B It

Model
Likes
Downloads
VRAM
Gemma 7B It GGUF111733 GB
Gemma 7B It GGUF71713 GB

Best Alternatives to Gemma 7B It

Best Alternatives
Context / RAM
Downloads
Likes
Gemma 7B8K / 17.1 GB594913076
Gemma 1.1 7B It GGUF8K / 5.3 GB241
Train068K / 9.1 GB160
Llama2 Kazakh 7B GGUF8K / 4.1 GB160
Gemma 7B8K / 17.1 GB130
Gemma 7B Translator 0.48K / 17.1 GB350
Gemma 7B Translator 0.38K / 17.1 GB230
Gemma7B Konosuba8K / 17.1 GB230
Gemma 7B It GGUF8K / 5.3 GB161
Gemma 7B It GGUF8K / 3.1 GB17311

Rank the Gemma 7B It 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? 40013 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 v20241217
  Support LLM Explorer