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Nsql 2B by NumbersStation

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  Autotrain compatible   Codegen   Endpoints compatible   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/NumbersStation/nsql-2B 

Nsql 2B Benchmarks

LLME Score: 0.11494
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Nsql 2B (NumbersStation/nsql-2B)

Nsql 2B Parameters and Internals

Model Type 
autoregressive, text-to-SQL generation
Use Cases 
Areas:
SQL generation tasks
Applications:
Database querying, Natural language to SQL conversion
Primary Use Cases:
Text-to-SQL generation, Database query formation
Considerations:
The model should be used with the defined prompt format for optimal results.
Additional Notes 
Model is fine-tuned for SQL generation with predefined prompt format and designed to output SELECT queries.
Training Details 
Data Sources:
The Stack, 20 public sources for text-to-SQL pairs
Data Volume:
1M training samples from The Stack
Methodology:
Cross-entropy loss for SQL generation tasks
Hardware Used:
80GB A100s
Model Architecture:
Autoregressive model
LLM NameNsql 2B
Repository 🤗https://huggingface.co/NumbersStation/nsql-2B 
Model Size2b
Required VRAM11.3 GB
Updated2025-02-22
MaintainerNumbersStation
Model Typecodegen
Model Files  10.1 GB: 1-of-2   1.2 GB: 2-of-2   10.1 GB: 1-of-2   1.2 GB: 2-of-2
Generates CodeYes
Model ArchitectureCodeGenForCausalLM
Licensebsd-3-clause
Model Max Length2048
Transformers Version4.28.1
Tokenizer ClassGPT2Tokenizer
Vocabulary Size51200
Torch Data Typefloat32
Activation Functiongelu_new

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Note: green Score (e.g. "73.2") means that the model is better than NumbersStation/nsql-2B.

Rank the Nsql 2B 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  
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Code Generation  
Multi-Language Support and Translation  

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Release v20241227
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