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Gemma 2 2B It Test by xufofox

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Gemma 2 2B It Test is an open-source language model by xufofox. Features: 2b LLM, VRAM: 5.2GB, Context: 8K, License: gemma, LLM Explorer Score: 0.15.

  Arxiv:1705.03551   Arxiv:1804.06876   Arxiv:1804.09301   Arxiv:1809.02789   Arxiv:1811.00937   Arxiv:1903.00161   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   Arxiv:2403.13793   Autotrain compatible   Conversational   Endpoints compatible   Gemma2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/xufofox/gemma-2-2b-it-test 

Gemma 2 2B It Test Benchmarks

LLME Score: 0.14969
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma 2 2B It Test (xufofox/gemma-2-2b-it-test)
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Gemma 2 2B It Test Parameters and Internals

Model Type 
text-to-text, decoder-only, large language model
Use Cases 
Areas:
Research, Commercial Applications
Applications:
Text Generation, Chatbots and Conversational AI, Text Summarization
Primary Use Cases:
Content Creation and Communication, Research and Education
Limitations:
Context and Task Complexity, Language Ambiguity, Factual Inaccuracies
Considerations:
Adhering to privacy regulations, continuous monitoring for bias, content safety mechanisms.
Additional Notes 
Training used multilingual, diverse data including code and mathematics.
Supported Languages 
English (Fluent)
Training Details 
Data Sources:
Web Documents, Code, Mathematics
Data Volume:
2 trillion tokens for 2B model
Methodology:
Text-to-text, decoder-only
Hardware Used:
TPUv5p
Model Architecture:
Lightweight state-of-the-art open model
Safety Evaluation 
Methodologies:
Red-teaming, Human evaluation, Automated evaluation
Risk Categories:
Misinformation, Bias, Dangerous capabilities, Memorization
Ethical Considerations:
Bias and fairness concerns, misinformation risks, transparency and accountability.
Responsible Ai Considerations 
Fairness:
Models evaluated for socio-cultural biases.
Transparency:
Summary details on architecture, capabilities, and limitations provided.
Accountability:
Guidelines provided for responsible use.
Mitigation Strategies:
Evaluations and automated techniques to filter sensitive data from training sets.
Input Output 
Input Format:
Text string
Accepted Modalities:
text
Output Format:
Generated English-language text
Performance Tips:
Better performance with clear prompts and instruction.
Release Notes 
Version:
2B
Notes:
Lightweight open model, trained on 2 trillion tokens.
LLM NameGemma 2 2B It Test
Repository 🤗https://huggingface.co/xufofox/gemma-2-2b-it-test 
Model Size2b
Required VRAM5.2 GB
Updated2025-09-14
Maintainerxufofox
Model Typegemma2
Model Files  5.0 GB: 1-of-2   0.2 GB: 2-of-2
Model ArchitectureGemma2ForCausalLM
Licensegemma
Context Length8192
Model Max Length8192
Transformers Version4.42.4
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typebfloat16

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

Rank the Gemma 2 2B It Test 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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