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Nsql 350M by NumbersStation

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  Autotrain compatible   Codegen   Endpoints compatible   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/NumbersStation/nsql-350M 

Nsql 350M Benchmarks

LLME Score: 0.12044
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Nsql 350M (NumbersStation/nsql-350M)

Nsql 350M Parameters and Internals

Model Type 
autoregressive, SQL generation
Use Cases 
Primary Use Cases:
text-to-SQL generation tasks
Limitations:
Works best with prompt format defined for SELECT queries
Additional Notes 
The model works best with the prompt format defined below and outputting SELECT queries.
Training Details 
Data Sources:
The Stack, more than 20 public sources across the web
Data Volume:
1M training samples for general SQL queries
Methodology:
Pre-trained on a dataset of general SQL queries and fine-tuned on text-to-SQL pairs
Hardware Used:
80GB A100s
LLM NameNsql 350M
Repository 🤗https://huggingface.co/NumbersStation/nsql-350M 
Model Size350m
Required VRAM1.5 GB
Updated2025-02-22
MaintainerNumbersStation
Model Typecodegen
Model Files  1.5 GB
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-350M.

Rank the Nsql 350M 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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