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Codegemma 7B by unsloth

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  Autotrain compatible   Bnb   En   Endpoints compatible   Gemma   Region:us   Safetensors   Sharded   Tensorflow   Unsloth
Model Card on HF 🤗: https://huggingface.co/unsloth/codegemma-7b 

Codegemma 7B Benchmarks

LLME Score: 0.19544
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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Codegemma 7B Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
beginner-friendly fine-tuning and text generation
Applications:
finetuning models for faster and memory-efficient performance, exporting models to various formats, uploading models to Hugging Face
Primary Use Cases:
2x faster fine-tuning
Additional Notes 
Unsloth provides free Colab notebooks for beginners to finetune models efficiently.
LLM NameCodegemma 7B
Repository 🤗https://huggingface.co/unsloth/codegemma-7b 
Model Size7b
Required VRAM17 GB
Updated2025-06-11
Maintainerunsloth
Model Typegemma
Model Files  5.8 GB: 1-of-3   5.9 GB: 2-of-3   5.3 GB: 3-of-3
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
Codegemma 7B (unsloth/codegemma-7b)

Quantized Models of the Codegemma 7B

Model
Likes
Downloads
VRAM
Codegemma 7B AWQ0127 GB
CodeGemma 7B AWQ0187 GB

Best Alternatives to Codegemma 7B

Best Alternatives
Context / RAM
Downloads
Likes
Kaggle Math Model Gemma V112K / 17.1 GB190
Gemma 1.1 7B It8K / 17.1 GB17200273
SeaLLM 7B V2.58K / 17.1 GB1549649
Codegemma 7B8K / 17.1 GB177384192
Zephyr 7B Gemma DPO Avg8K / 17.1 GB150
Zephyr 7B Gemma Rpo Avg8K / 17.1 GB90
Zephyr 7B Gemma V0.18K / 17.1 GB938123
... Codegemma 2 7B It Alpaca V1.38K / 17.1 GB411
SauerkrautLM Gemma 7B8K / 17.1 GB389213
... 7B Finetuned Sft Navarasa 2.08K / 34 GB125119
Note: green Score (e.g. "73.2") means that the model is better than unsloth/codegemma-7b.

Rank the Codegemma 7B 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 v20241124
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