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Gemma 7B It by google

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  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

Gemma 7B It Benchmarks

LMSys ELO: 1038 vs 1272 (so35)-18.4%
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: 1.59
LLME Score: 0.5075
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 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
Updated2024-11-21
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 It (google/gemma-7b-it)

Quantized Models of the Gemma 7B It

Model
Likes
Downloads
VRAM
Gemma 7B It GGUF74343 GB
Gemma 7B It GGUF112373 GB

Best Alternatives to Gemma 7B It

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Context / RAM
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Likes
Gemma 7B8K / 17.1 GB2599923054
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

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  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241110
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