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CodeGemma 7B AWQ by TechxGenus

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  4-bit   Autotrain compatible   Awq   Code   Endpoints compatible   Gemma   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TechxGenus/CodeGemma-7b-AWQ 

CodeGemma 7B AWQ Benchmarks

ARC: 53.92 vs 96.7 (so35)-44.2%
HellaSwag: 76.73 vs 95.3 (gpt4)-19.5%
MMLU: 56.59 vs 88.3 (so35)-35.9%
TruthfulQA: 38.03 vs 59 (gpt4)-35.5%
WinoGrande: 69.61 vs 87.5 (gpt4)-20.4%
GSM8K: 45.49 vs 96.4 (so35)-52.8%
HumanEvalA: 30.6
Python Eva: 40.13 vs 92 (so35)-56.4%
Java Eval: 35.03
Javascript: 43.06
CPP Eval: 40.34
PHP Eval: 34.76
Julia Eval: 28.91
D Eval: 10.44
Lua Eval: 32.88
R Eval: 20.96
Racket Eva: 13.55
Rust Eval: 34.56
Swift Eval: 32.62
LLME Score: 0.19574
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
CodeGemma 7B AWQ (TechxGenus/CodeGemma-7b-AWQ)

CodeGemma 7B AWQ Parameters and Internals

Model Type 
text-generation, code generation
Use Cases 
Areas:
text generation, code generation
Primary Use Cases:
code generation, coding-related tasks
Limitations:
Model may produce errors, misleading contents, or struggle with non-coding tasks., Limited testing, requires additional safety evaluation.
Considerations:
Additional safety testing required for real-world deployment.
Supported Languages 
programming languages (Python)
Training Details 
Data Sources:
Gemma-7b base model , additional 0.7 billion high-quality, code-related tokens
Data Volume:
0.7 billion high-quality tokens
Methodology:
Fine-tuned with DeepSpeed ZeRO 3 and Flash Attention 2
Training Time:
3 epochs
Safety Evaluation 
Ethical Considerations:
Limited testing, additional safety testing recommended before real-world deployment.
Input Output 
Input Format:
Instruction format, Alpaca instruction format (excluding system prompt)
Accepted Modalities:
text
Output Format:
text
LLM NameCodeGemma 7B AWQ
Repository 🤗https://huggingface.co/TechxGenus/CodeGemma-7b-AWQ 
Base Model(s)  Codegemma 7B   unsloth/codegemma-7b
Model Size7b
Required VRAM7.2 GB
Updated2025-02-22
MaintainerTechxGenus
Model Typegemma
Model Files  6.6 GB: 1-of-2   0.6 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureGemmaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.39.0.dev0
Tokenizer ClassGemmaTokenizer
Padding Token<eos>
Vocabulary Size256000
Torch Data Typefloat16

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

Rank the CodeGemma 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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Release v20241227
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