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Gemma 1.1 7B It by unsloth

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Model Card on HF 🤗: https://huggingface.co/unsloth/gemma-1.1-7b-it 

Gemma 1.1 7B It Benchmarks

LLME Score: 0.17438
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma 1.1 7B It (unsloth/gemma-1.1-7b-it)

Gemma 1.1 7B It Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
research, commercial applications
Applications:
text generation, finetuning experiments
Primary Use Cases:
finetuning models with reduced memory and increased speed
Considerations:
Designed to be used with specific modification and fine-tuning tools.
Additional Notes 
The model can be exported to GGUF, vLLM, or uploaded to Hugging Face.
LLM NameGemma 1.1 7B It
Repository 🤗https://huggingface.co/unsloth/gemma-1.1-7b-it 
Model Size7b
Required VRAM17 GB
Updated2025-03-18
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

Quantized Models of the Gemma 1.1 7B It

Model
Likes
Downloads
VRAM
Gemma 1.1 7B It GGUF1695 GB
Gemma 1.1 7B It GPTQ167 GB
Gemma 1.1 7B It 4bit4115 GB
Gemma 1.1 7B It AWQ057 GB
Gemma 1.1 7B It 4bit175 GB

Best Alternatives to Gemma 1.1 7B It

Best Alternatives
Context / RAM
Downloads
Likes
Kaggle Math Model Gemma V112K / 17.1 GB100
Gemma 1.1 7B It8K / 17.1 GB17912270
Zephyr 7B Gemma Rpo Avg8K / 17.1 GB430
SeaLLM 7B V2.58K / 17.1 GB1133049
Zephyr 7B Gemma DPO Avg8K / 17.1 GB150
... 7B Finetuned Sft Navarasa 2.08K / 34 GB2777018
... Codegemma 2 7B It Alpaca V1.38K / 17.1 GB121
Zephyr 7B Gemma V0.18K / 17.1 GB591124
SauerkrautLM Gemma 7B8K / 17.1 GB302813
Codegemma 7B8K / 17.1 GB3645179
Note: green Score (e.g. "73.2") means that the model is better than unsloth/gemma-1.1-7b-it.

Rank the Gemma 1.1 7B It 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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