212 lines
6.4 KiB
Markdown
212 lines
6.4 KiB
Markdown
---
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license: llama3
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base_model: meta-llama/Meta-Llama-3.1-8B
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language:
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- en
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- zh
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- es
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pipeline_tag: text-generation
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tags:
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- code
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- spatial
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- sql
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- GIS
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- PostGIS
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inference: false
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---
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### Model Information
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This model, Llama-3.1-8B-Instruct-Spatial-SQL-1.0, is an 8B, narrow use case, text to spatial SQL, lightly fine-tuned model. In general, its primary use case
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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.
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There are four primary geographic functions released in version 1.0.
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**Model developer**: Mark Rodrigo
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**Github**: https://github.com/mprodrigo/spatialsql
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**Docker**: https://hub.docker.com/r/kartoza/postgis
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**Model Context Protocol (MCP)**: https://github.com/modelcontextprotocol/servers/tree/main/src/postgres
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**Model Architecture**: The model is a QLoRA / Supervised Fine Tuning (SFT)
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### Model Input / Output Overview:
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Input: Text plus coordinate prompt injection.
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</br>
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Output: **PostGIS spatial SQL**
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</br>
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NOTE: Inputs and outputs are in meters and or geographic decimal degrees WGS 84 coordinates.
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| Function | Question Input | Geo Input | SQL Execution Output |
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|:---------:|:---------------:|:---------:|:-------------------------:|
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| Area | Area question | Polygon | Number - Area sq meters |
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| Centroid | Center question | Polygon | Point |
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| Buffer | Buffer distance | Point | Polygon |
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| Length | Length question | Line | Number - Length in meters |
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### Example Prompt / Prompt File
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>
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<p></p>
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You are a helpful assistant. You are an expert at PostGIS and Postgresql and SQL and psql.
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<p></p>
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<|eot_id|><|start_header_id|>user<|end_header_id|>
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\### Instruction: Write a PostGIS SQL statement for the following.
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<p></p>
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\### Input:
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<p></p>
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{input}
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<p></p>
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\### Response:
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<|eot_id|><|start_header_id|>assistant<|end_header_id|>
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### Examples
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AREA
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<p></p>
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\### 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))'
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<p></p>
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\### Input: ¿Cuál es el área para el polígono? : 'Polygon ((-3.7515154 40.3855551, -3.7514972 40.3856581, -3.7507005 40.3855767, -3.7507167 40.3854722, -3.7515154 40.3855551))'
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<p></p>
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\### Input: 多邊形的面積是多少？ : 'Polygon ((-3.7515154 40.3855551, -3.7514972 40.3856581, -3.7507005 40.3855767, -3.7507167 40.3854722, -3.7515154 40.3855551))'
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<p></p>
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\### 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;
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<p></p>
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CENTROID
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<p></p>
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\### 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))'
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<p></p>
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\### Input: ¿Cuál es el centroide del polígono? : 'Polygon ((-3.6934636 40.4808785, -3.6933352 40.4811486, -3.6930125 40.4810598, -3.693141 40.4807897, -3.6934636 40.4808785))'
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<p></p>
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### Input: 多邊形的質心是什麼？ : 'Polygon ((-3.6934636 40.4808785, -3.6933352 40.4811486, -3.6930125 40.4810598, -3.693141 40.4807897, -3.6934636 40.4808785))'
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<p></p>
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\### 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;
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<p></p>
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BUFFER
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<p></p>
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\### Input: What is the thousand meter buffer for the following point? : 'Point(-8.7522658 41.3862664)'
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<p></p>
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\### Input: ¿Cuál es el buffer de mil metros para lo siguiente punto? : 'Point(-8.7522658 41.3862664)'
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<p></p>
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\### Input: 以下點的千米緩衝區是多少？ : 'Point(-8.7522658 41.3862664)'
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<p></p>
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\### Response: SELECT ST_AsText(ST_Buffer(geog, 1000)) as buffer FROM (select 'Point(-8.7522658 41.3862664)' :: geography geog) subquery;
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<p></p>
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LENGTH
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<p></p>
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\### Input: How long is the line? : 'LINESTRING (-3.6976693 40.4263178, -3.6986082 40.4258729)'
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<p></p>
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\### Input: ¿Cuánto dura la línea? : 'LINESTRING (-3.6976693 40.4263178, -3.6986082 40.4258729)'
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<p></p>
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\### Input: 隊伍有多長？ : 'LINESTRING (-3.6976693 40.4263178, -3.6986082 40.4258729)'
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<p></p>
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\### Response: SELECT ST_Length(geog) As length FROM (select 'LINESTRING (-3.6976693 40.4263178, -3.6986082 40.4258729)' :: geography geog) subquery;
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<p></p>
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### A Few Known Question Variation Examples
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<p></p>
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AREA
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<p></p>
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What is the area for the geometry?
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<p></p>
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What is the area for this polygon?
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<p></p>
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CENTROID
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<p></p>
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What is the centroid for the geometry?
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<p></p>
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What is the center point of the polygon?
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<p></p>
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BUFFER
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<p></p>
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What is the 100 meter buffer for the following point?
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<p></p>
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Buffer the following point a thousand meters.
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<p></p>
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What is the 1000 meter buffer for the following point?
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<p></p>
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LENGTH
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<p></p>
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What is the length of the line?
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<p></p>
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How long is this line?
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### llama.cpp / Hyperparameter Recommendations For Inference
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max context ~ 8,000 or lower
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<p></p>
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top k ~ 100
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<p></p>
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temp ~ .4-.5 or lower
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### Agent Considerations
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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.
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### Further Reference - link this
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https://postgis.net/docs/manual-3.3/PostGIS_Special_Functions_Index.html#PostGIS_GeographyFunctions
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### Evaluation data
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More information needed
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### Training data
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Custom synthetic
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-04
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- train_batch_size: 10
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- eval_batch_size: 3
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- distributed_type: multi-GPU
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- num_devices: 2
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- optimizer: Adam 8bit
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- lr_scheduler_type: linear
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- num_epochs: 3
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### Training results
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| Training Loss | Step | Validation Loss |
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|:-------------:|:----:|:---------------:|
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| 0.5438 | 10 | 0.5247 |
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| 0.4889 | 20 | 0.4494 |
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| 0.4072 | 30 | 0.4051 |
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### Framework versions
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- Transformers 4.44.0
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- Pytorch 2.4.0
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- peft 0.12.0
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- Datasets 2.21.0
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- Tokenizers 0.19.1 |