Google Gemma 2 9B It by SillyTilly

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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:2103.03874   Arxiv:2107.03374   Arxiv:2108.07732   Arxiv:2109.07958   Arxiv:2110.08193   Arxiv:2110.14168   Arxiv:2203.09509   Arxiv:2206.04615   Arxiv:2304.06364   Autotrain compatible   Conversational   Endpoints compatible   Gemma2   Region:us   Safetensors   Sharded   Tensorflow

Google Gemma 2 9B It Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Google Gemma 2 9B It Parameters and Internals

Model Type
text-to-text, decoder-only, large language model
Use Cases
Areas:
Research, Commercial applications
Applications:
Content Creation and Communication, Research and Education
Primary Use Cases:
Text Generation, Chatbots and Conversational AI, Text Summarization
Limitations:
Open-ended or highly complex tasks, Language ambiguity and nuance, Factual inaccuracy, Common sense reasoning
Additional NotesTrained using JAX and ML Pathways.
Supported Languages
English (Full Support)
Training Details
Data Sources:
Web Documents, Code, Mathematics
Data Volume:8 trillion tokens
Hardware Used:
TPUv5p
Safety Evaluation
Methodologies:
Red-teaming, Internal evaluations
Findings:
Within acceptable thresholds for internal policies
Risk Categories:
Text-to-Text Content Safety, Text-to-Text Representational Harms, Memorization, Large-scale harm
Responsible Ai Considerations
Fairness:Careful scrutiny and pre-processing of input data
Transparency:Model card summarizes the model's details
Accountability:Model creators accountable for evaluation processes
Mitigation Strategies:Continuous monitoring and exploration of de-biasing techniques
Input Output
Input Format:Text string
Accepted Modalities:
text
Output Format:Generated English-language text
Performance Tips:Use bfloat16 or float16 for better performance on compatible hardware.
LLM NameGoogle Gemma 2 9B It
Repository ๐Ÿค—https://huggingface.co/SillyTilly/google-gemma-2-9b-it 
Model Size9b
Required VRAM18.6 GB
Updated2024-11-13
MaintainerSillyTilly
Model Typegemma2
Model Files  4.9 GB: 1-of-4   5.0 GB: 2-of-4   5.0 GB: 3-of-4   3.7 GB: 4-of-4
Model ArchitectureGemma2ForCausalLM
Licensegemma
Context Length8192
Model Max Length8192
Transformers Version4.42.0.dev0
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typebfloat16
Google Gemma 2 9B It (SillyTilly/google-gemma-2-9b-it)

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Note: green Score (e.g. "73.2") means that the model is better than SillyTilly/google-gemma-2-9b-it.

Rank the Google Gemma 2 9B It 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241110