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Sqlcoder 7B AWQ by TheBloke

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  4-bit   Autotrain compatible   Awq   Base model:defog/sqlcoder-7b Base model:quantized:defog/sql...   Code   En   Mistral   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/sqlcoder-7B-AWQ 

Sqlcoder 7B AWQ Benchmarks

LLME Score: 0.12131
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Sqlcoder 7B AWQ (TheBloke/sqlcoder-7B-AWQ)
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Sqlcoder 7B AWQ Parameters and Internals

Model Type 
mistral, text-generation
Use Cases 
Areas:
research, commercial applications
Applications:
natural language to SQL generation
Primary Use Cases:
SQL query generation from natural language questions
Supported Languages 
en (proficient)
Training Details 
Data Sources:
human-curated questions based on 10 different schemas
Data Volume:
more than 20,000 questions
Hardware Used:
A100 40GB GPU with `bfloat16` weights
Model Architecture:
fine-tuned on a base Mistral-7B model
LLM NameSqlcoder 7B AWQ
Repository 🤗https://huggingface.co/TheBloke/sqlcoder-7B-AWQ 
Model NameSQLCoder 7B
Model CreatorDefog.ai
Base Model(s)  Sqlcoder 7B   defog/sqlcoder-7b
Model Size7b
Required VRAM4.2 GB
Updated2025-09-23
MaintainerTheBloke
Model Typemistral
Model Files  4.2 GB
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMistralForCausalLM
Licensecc-by-sa-4.0
Context Length32768
Model Max Length32768
Transformers Version4.35.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/sqlcoder-7B-AWQ.

Rank the Sqlcoder 7B AWQ 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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Release v20241124
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