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Gemma 2B by google

 »  All LLMs  »  google  »  Gemma 2B   URL Share it on

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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   Endpoints compatible   Gemma   Gguf   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/google/gemma-2b 

Gemma 2B Benchmarks

MMLU Pro: 4.06
GPQA: 0.67
MUSR: 7.56
BBH: 8.47
IFEval: 20.38 vs 88 (so35)-76.8%
ARC: 48.38 vs 96.7 (so35)-50%
HellaSwag: 71.77 vs 95.3 (gpt4)-24.7%
MMLU: 41.77 vs 88.3 (so35)-52.7%
TruthfulQA: 33.08 vs 59 (gpt4)-43.9%
WinoGrande: 66.3 vs 87.5 (gpt4)-24.2%
GSM8K: 16.91 vs 96.4 (so35)-82.5%
MATH Lvl 5: 3.02
LLME Score: 0.4159
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma 2B (google/gemma-2b)

Gemma 2B Parameters and Internals

Model Type 
text-to-text, decoder-only, large language model
Use Cases 
Areas:
Various industries and domains
Applications:
Content Creation and Communication, Research and Education
Primary Use Cases:
Text Generation, Chatbots and Conversational AI, Text Summarization, NLP Research, Language Learning, Knowledge Exploration
Limitations:
Bias and Fairness, Misinformation and Misuse, Lack of Common Sense, Factual Inaccuracy
Considerations:
LLMs performance is heavily dependent on the quality of input prompts and the context length.
Additional Notes 
This description is based on the specified version, other iteration details can be found in technical documents.
Supported Languages 
English (available for text generation, question answering, summarization, and reasoning tasks)
Training Details 
Data Sources:
Web Documents, Code, Mathematics
Data Volume:
6 trillion tokens
Methodology:
Rigorous CSAM filtering, Sensitive Data Filtering, filtering based on content quality and safety
Context Length:
8192
Hardware Used:
TPUv5e, TPU Pods
Model Architecture:
JAX and ML Pathways
Safety Evaluation 
Methodologies:
Red-teaming, Structured evaluations
Risk Categories:
Text-to-Text Content Safety, Text-to-Text Representational Harms, Memorization, Large-scale harm
Ethical Considerations:
Models evaluated against a number of different categories relevant to ethics and safety, include Text-to-Text Content Safety, Representational Harms, potential data memorization, and dangerous capability tests.
Responsible Ai Considerations 
Fairness:
These models underwent careful scrutiny and input data pre-processing with posterior evaluations reported in this card.
Transparency:
The model card summarizes details on the models' architecture, capabilities, limitations, and evaluation processes.
Accountability:
Google is accountable for the use of the model under its terms of service and policies.
Mitigation Strategies:
Developers are encouraged to monitor and report misuse, employ de-biasing techniques, implement content safety safeguards, and adhere to privacy regulations.
Input Output 
Input Format:
Text string
Accepted Modalities:
text
Output Format:
Generated English-language text
Performance Tips:
Ensure to use correct input formats for fine-tuning or inference, use optimizations for specific hardware and quantization methods.
Release Notes 
Version:
v1.1 IT
Notes:
Contains updates and new numbers for the IT version models, surpasses previous versions across various benchmarks.
LLM NameGemma 2B
Repository 🤗https://huggingface.co/google/gemma-2b 
Base Model(s)  Google Gemma 2B 1719012541   richardkelly/google-gemma-2b-1719012541
Model Size2b
Required VRAM5.1 GB
Updated2024-12-22
Maintainergoogle
Model Typegemma
Model Files  10.0 GB   5.0 GB: 1-of-2   0.1 GB: 2-of-2
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 2B

Model
Likes
Downloads
VRAM
Octopus V2 Gguf AWQ713331 GB
Gemma 2B GGUF01271 GB
Gemma 2B GGUF61501 GB
Physicsgemma2bAlpaca0112 GB

Best Alternatives to Gemma 2B

Best Alternatives
Context / RAM
Downloads
Likes
Gemma 2B It8K / 5.1 GB91565685
Gemma 2B It8K / 1.5 GB130
Gemma 2B It8K / 5.1 GB191
Gemma 2B T8K / 5.1 GB130
Gemma 2B It Code8K / 5.1 GB200
Gemma 2B It Q8K / 1.6 GB91
...mma 2b Sauerkraut Gguf Chunked8K / 0.1 GB420
Gemma 2B It GGUF8K / 0.9 GB21884
G2ft V28K / 5 GB140
Gemma Reformat Text Finetune8K / 5.1 GB120
Note: green Score (e.g. "73.2") means that the model is better than google/gemma-2b.

Rank the Gemma 2B 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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Release v20241217
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