README.md

---
license: apache-2.0
base_model: Qwen/Qwen3.5-4B
pipeline_tag: text-generation
tags:
- code
- spatial
- sql
- GIS
- PostGIS
---

### Model Information

This model, Qwen-3.5-4B-Instruct-Spatial-SQL-1.1, is an 4B, 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 ten geographic functions released in version 1.2.

**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:

### Example Prompt / Prompt File

### Examples

### A Few Known Question Variation Examples

### llama.cpp / Hyperparameter Recommendations For Inference

### Agent Considerations

### Further Reference - link this

### Evaluation data

### Training data
Custom synthetic

### Training hyperparameters

### Training results

| Training Loss | Step | Validation Loss |
|:-------------:|:----:|:---------------:|
| 1.1217        |  10  |   0.8837        |
| 0.8026        |  20  |   0.7469        |
| 0.7432        |  30  |   0.6925        |
| 0.6930        |  40  |   0.6455        |
| 0.6189        |  50  |   0.5935        |
| 0.5665        |  60  |   0.5342        |
| 0.4824        |  70  |   0.4802        |
| 0.4461        |  80  |   0.4557        |

### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1
- peft 0.19.1
- Datasets 5.0.0
- Tokenizers 0.22.2