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---
license: llama3.2
base_model: meta-llama/Meta-Llama-3.2-1B
language:
- en
pipeline_tag: text-generation
tags:
- code
- spatial
- sql
- GIS
- PostGIS
---
**ENGLISH ONLY - Use 8b models for alternate languages.**
### Model Information
This model, Llama-3.2-1B-Instruct-Spatial-SQL-1.0, is an 1B, narrow use case, text to spatial SQL, lightly fine-tuned model. In general, its primary use case
is the Natural Language command adaptation of particular geographic spatial functions as normally defined in pure SQL. Data input should be a combination of an English prefix in the form of a question, and a coordinate prompt injection, likely from an active mapping system application coordinate list. Output is PostGIS spatial SQL.
There are four primary geographic functions released in version 1.0.
**Model developer**: Mark Rodrigo
**Github**: https://github.com/mprodrigo/spatialsql
**Model Architecture**: The model is a QLoRA / Supervised Fine Tuning (SFT)
### Model Input / Output Overview:
Input: Text plus coordinate prompt injection.
</br>
Output: **PostGIS spatial SQL**
</br>
NOTE: Inputs and outputs are in meters and or geographic decimal degrees WGS 84 coordinates.
| Function | Question Input | Geo Input | SQL Execution Output |
|:---------:|:---------------:|:---------:|:-------------------------:|
| Area | Area question | Polygon | Number - Area sq meters |
| Centroid | Center question | Polygon | Point |
| Buffer | Buffer distance | Point | Polygon |
| Length | Length question | Line | Number - Length in meters |
### Example Prompt / Prompt File
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
<p></p>
You are a helpful assistant. You are an expert at PostGIS and Postgresql and SQL and psql.
<p></p>
<|eot_id|><|start_header_id|>user<|end_header_id|>
\### Instruction: Write a PostGIS SQL statement for the following.
<p></p>
\### Input:
<p></p>
{input}
<p></p>
\### Response:
<|eot_id|><|start_header_id|>assistant<|end_header_id|>
### Examples
AREA
<p></p>
\### Input: What is the area for the polygon? : 'Polygon ((-3.7515154 40.3855551, -3.7514972 40.3856581, -3.7507005 40.3855767, -3.7507167 40.3854722, -3.7515154 40.3855551))'
<p></p>
\### Response: SELECT ST_Area(geog) As area FROM (select 'Polygon ((-3.7515154 40.3855551, -3.7514972 40.3856581, -3.7507005 40.3855767, -3.7507167 40.3854722, -3.7515154 40.3855551))' :: geography geog) subquery;
<p></p>
CENTROID
<p></p>
\### Input: What is the centroid for the polygon? : 'Polygon ((-3.6934636 40.4808785, -3.6933352 40.4811486, -3.6930125 40.4810598, -3.693141 40.4807897, -3.6934636 40.4808785))'
<p></p>
\### Response: SELECT ST_AsText(ST_Centroid(geog)) As centroid FROM (select 'Polygon ((-3.6934636 40.4808785, -3.6933352 40.4811486, -3.6930125 40.4810598, -3.693141 40.4807897, -3.6934636 40.4808785))' :: geography geog) subquery;
BUFFER
<p></p>
\### Input: What is the thousand meter buffer for the following point? : 'Point(-8.7522658 41.3862664)'
<p></p>
\### Response: SELECT ST_AsText(ST_Buffer(geog, 1000)) as buffer FROM (select 'Point(-8.7522658 41.3862664)' :: geography geog) subquery;
<p></p>
LENGTH
<p></p>
\### Input: How long is the line? : 'LINESTRING (-3.6976693 40.4263178, -3.6986082 40.4258729)'
<p></p>
\### Response: SELECT ST_Length(geog) As length FROM (select 'LINESTRING (-3.6976693 40.4263178, -3.6986082 40.4258729)' :: geography geog) subquery;
<p></p>
### A Few Known Question Variation Examples
<p></p>
AREA
<p></p>
What is the area for the geometry?
<p></p>
What is the area for this polygon?
<p></p>
CENTROID
<p></p>
What is the centroid for the geometry?
<p></p>
What is the center point of the polygon?
<p></p>
BUFFER
<p></p>
What is the 100 meter buffer for the following point?
<p></p>
Buffer the following point a thousand meters.
<p></p>
What is the 1000 meter buffer for the following point?
<p></p>
LENGTH
<p></p>
What is the length of the line?
<p></p>
How long is this line?
### llama.cpp / Hyperparameter Recommendations For Inference
max context ~ 8,000 or lower
<p></p>
top k ~ 100 or lower
<p></p>
temp ~ .4-.7 or lower
### Agent Considerations
Agents are being considered as a separate project. Agents would mostly be related to pulling the coordinates from a mapping UI, and executing the SQL from responses against a PostGIS database.
### Further Reference - link this
https://postgis.net/docs/manual-3.3/PostGIS_Special_Functions_Index.html#PostGIS_GeographyFunctions
### Evaluation data
More information needed
### Training data
Custom synthetic
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 10
- eval_batch_size: 3
- distributed_type: multi-GPU
- num_devices: 2
- optimizer: Adam 8bit
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.9106 | 20 | 10 | 1.9183 |
| 1.1674 | 20 | 20 | 1.1710 |
| 0.7446 | 20 | 30 | 0.7589 |
| 0.6143 | 20 | 40 | 0.6220 |
| 0.5773 | 20 | 50 | 0.5695 |
| 0.5328 | 20 | 60 | 0.5334 |
| 0.5146 | 20 | 70 | 0.5096 |
| 0.4895 | 20 | 80 | 0.4925 |
| 0.4893 | 20 | 90 | 0.4772 |
| 0.4710 | 20 | 100 | 0.4612 |
| 0.4572 | 20 | 110 | 0.4438 |
| 0.4358 | 20 | 120 | 0.4233 |
| 0.4002 | 20 | 130 | 0.4014 |
| 0.3812 | 20 | 140 | 0.3768 |
| 0.3461 | 20 | 150 | 0.3492 |
| 0.3222 | 20 | 160 | 0.3202 |
| 0.3043 | 20 | 170 | 0.2921 |
| 0.2727 | 20 | 180 | 0.2651 |
| 0.2378 | 20 | 190 | 0.2403 |
| 0.2229 | 20 | 200 | 0.2184 |
| 0.2121 | 20 | 210 | 0.1990 |
| 0.1891 | 20 | 220 | 0.1834 |
| 0.1867 | 20 | 230 | 0.1723 |
| 0.1848 | 20 | 240 | 0.1654 |
| 0.1732 | 20 | 250 | 0.1631 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.5.0
- peft 0.13.2
- Datasets 3.0.1
- Tokenizers 0.20.1