Text To Sql - AI Text to SQL Generator Model
Text to SQL Generator
by Neurometric AI⚙️ Engineering & Product
Specialized model that converts natural language questions into optimized SQL queries. Designed for high-accuracy SQL generation at lower cost and faster speed than general-purpose LLMs.
Text To Sql is designed for Engineering & Product workflows where speed, consistency, and control matter more than generic creativity. Instead of relying on a broad model to guess intent each time, this task-specific SLM is optimized for text to sql generator and predictable output quality. That makes it easier to adopt in production pipelines where teams need reliable formatting, lower latency, and reduced hallucination risk.
Engineering teams usually pair issue trackers, pull request metadata, and CI logs from GitHub, GitLab, and Linear. This makes deployment practical for sales ops, customer success, legal, and operations teams that need answers grounded in their own data. Because the model is small and focused, teams can run it with efficient infrastructure while still meeting quality targets for the use case.
Compared with general-purpose models, focused SLMs like this one typically deliver better precision for narrow tasks, lower cost per request, and easier governance. You can start with the free tier, test the model against your business data, and scale usage through Neurometric APIs or ClawPack workflows when performance meets your benchmark.
Model: qwen3-4b
This task-specific SLM uses qwen3-4b with a specialized system prompt. The model weights are identical to the base Qwen model — the task specialization comes from the system prompt and has been validated through our testing pipeline. Need better accuracy? We can fine-tune the model on your data for your specific use case.
Quickstart
Copy-paste code to use Text to SQL Generator in your project
from openai import OpenAI
client = OpenAI(
base_url="https://api.neurometric.ai/v1",
api_key="YOUR_API_KEY"
)
resp = client.chat.completions.create(
model="neurometric/text-to-sql",
messages=[
{"role": "user",
"content": "Your input here"}
]
)
print(resp.choices[0].message.content)Test this model
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Capabilities
Related models
Frequently asked questions
Does Text To Sql work with CRM systems?
Yes. Text To Sql is built to work with CRM systems, internal docs, and CSV/JSON pipelines. Most teams connect existing APIs or scheduled exports and map records into prompt-ready JSON.
What data format does this model accept?
You can send plain text or structured JSON. For text to sql generator, teams usually pass normalized records with field names, context notes, and output constraints.
Why use a task-specific SLM for text to sql generator?
Task-specific SLMs are tuned for one business outcome, so they are often more consistent and cost-efficient than general models for repetitive production workflows.
Try This Model
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Use via API
FreeView API settings and get a free key. Sign up when you want more keys or billing access.
Need better performance?
We can fine-tune this model on your data for higher accuracy on your specific use case.