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Gemma Ko 7B AWQ by ghost613

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  4-bit   Autotrain compatible   Awq   En   Endpoints compatible   Gemma   Ko   Pytorch   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/ghost613/gemma-ko-7b-AWQ 

Gemma Ko 7B AWQ Benchmarks

LLME Score: 0.19337
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma Ko 7B AWQ (ghost613/gemma-ko-7b-AWQ)

Gemma Ko 7B AWQ Parameters and Internals

Model Type 
text-generation
Additional Notes 
Quantized model from beomi/gemma-ko-7b. Original Gemma model page available.
Supported Languages 
ko (proficient), en (proficient)
LLM NameGemma Ko 7B AWQ
Repository 🤗https://huggingface.co/ghost613/gemma-ko-7b-AWQ 
Model Size7b
Required VRAM5.6 GB
Updated2025-02-22
Maintainerghost613
Model Typegemma
Model Files  5.0 GB: 1-of-2   0.6 GB: 2-of-2
Supported Languagesko en
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureGemmaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.41.1
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than ghost613/gemma-ko-7b-AWQ.

Rank the Gemma Ko 7B AWQ 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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