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Sqlcoder2 GGUF by TheBloke

 »  All LLMs  »  TheBloke  »  Sqlcoder2 GGUF   URL Share it on

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  Base model:defog/sqlcoder2 Base model:quantized:defog/sql...   Code   En   Gguf   Quantized   Region:us   Starcoder
Model Card on HF 🤗: https://huggingface.co/TheBloke/sqlcoder2-GGUF 

Sqlcoder2 GGUF Benchmarks

LLME Score: 0.14608
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Sqlcoder2 GGUF (TheBloke/sqlcoder2-GGUF)

Sqlcoder2 GGUF Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Research, Commercial applications
Applications:
Natural language to SQL query conversion
Primary Use Cases:
Generate SQL queries from natural language questions.
Limitations:
Potential untested or unexplored schemas.
Considerations:
Fine-tuning on specific schemas enhances performance.
Additional Notes 
The model's performance benefits from training on diverse schemas, and there are plans to enhance it with advanced training techniques.
Supported Languages 
English (High proficiency)
Training Details 
Data Sources:
20,000 human-curated questions based on 10 different schemas
Data Volume:
20,000 questions
Methodology:
Fine-tuned from StarCoder.
Input Output 
Input Format:
Natural language questions
Accepted Modalities:
text
Output Format:
SQL queries
Performance Tips:
Fine-tuning on a specific database schema can improve accuracy.
LLM NameSqlcoder2 GGUF
Repository 🤗https://huggingface.co/TheBloke/sqlcoder2-GGUF 
Model NameSqlcoder2
Model CreatorDefog.ai
Base Model(s)  Sqlcoder2   defog/sqlcoder2
Required VRAM6.7 GB
Updated2025-02-22
MaintainerTheBloke
Model Typestarcoder
Model Files  6.7 GB   9.1 GB   8.2 GB   6.9 GB   9.0 GB   10.0 GB   9.1 GB   10.9 GB   11.5 GB   10.9 GB   13.0 GB   16.8 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModel
Licenseother

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/sqlcoder2-GGUF.

Rank the Sqlcoder2 GGUF Capabilities

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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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