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Gemma 2B by unsloth

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  Autotrain compatible   En   Endpoints compatible   Gemma   Gemma-2b   Region:us   Safetensors   Unsloth
Model Card on HF 🤗: https://huggingface.co/unsloth/gemma-2b 

Gemma 2B Benchmarks

LLME Score: 0.20426
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma 2B (unsloth/gemma-2b)

Gemma 2B Parameters and Internals

Model Type 
Text Generation, Language Models
Use Cases 
Areas:
Research, Commercial Applications
Applications:
Finetuning language models quickly and efficiently
Primary Use Cases:
Model finetuning with reduced memory and faster performance
Considerations:
The model finetuning process may have limitations based on the dataset and hardware used.
Additional Notes 
The model supports quick and efficient finetuning through pre-developed notebooks accessible on platforms like Colab and Kaggle.
Input Output 
Accepted Modalities:
Text
Performance Tips:
Ensure optimal hardware setup to maximize performance benefits.
LLM NameGemma 2B
Repository 🤗https://huggingface.co/unsloth/gemma-2b 
Model Size2b
Required VRAM5 GB
Updated2025-02-05
Maintainerunsloth
Model Typegemma
Model Files  5.0 GB
Supported Languagesen
Model ArchitectureGemmaForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.44.2
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typebfloat16

Quantized Models of the Gemma 2B

Model
Likes
Downloads
VRAM
Gemma Han 2B0505 GB

Best Alternatives to Gemma 2B

Best Alternatives
Context / RAM
Downloads
Likes
Gemma 1.1 2B It8K / 5.1 GB93340154
Codegemma 2B8K / 5.1 GB853778
Gemma Ko 1.1 2B It8K / 5.1 GB23911
EMO 2B8K / 5.1 GB43042
Octopus V28K / 5.1 GB935872
Gemma2b Lungcancerqa8K / 3.1 GB842
LION Gemma 2B Sft V1.08K / 5.1 GB1040
Gemma 2B Orpo8K / 5.1 GB14828
2B Or Not 2B8K / 5.1 GB5426
Gemma 2B Ko V08K / 5 GB2230
Note: green Score (e.g. "73.2") means that the model is better than unsloth/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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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