markrodrigo
/

Llama-3.2-3B-Instruct-Spatial-SQL-1.1

@@ -1,199 +1,212 @@
 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-### Model Sources [optional]
-<!-- Provide the basic links for the model. -->
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-## Uses
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-### Direct Use
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-[More Information Needed]
-### Downstream Use [optional]
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-[More Information Needed]
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-[More Information Needed]
-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-[More Information Needed]
-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-## How to Get Started with the Model
-Use the code below to get started with the model.
-[More Information Needed]
-## Training Details
-### Training Data
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-[More Information Needed]
-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-#### Preprocessing [optional]
-[More Information Needed]
-#### Training Hyperparameters
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-#### Speeds, Sizes, Times [optional]
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-[More Information Needed]
-## Evaluation
-<!-- This section describes the evaluation protocols and provides the results. -->
-### Testing Data, Factors & Metrics
-#### Testing Data
-<!-- This should link to a Dataset Card if possible. -->
-[More Information Needed]
-#### Factors
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-[More Information Needed]
-#### Metrics
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-[More Information Needed]
-### Results
-[More Information Needed]
-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
-[More Information Needed]
-## Environmental Impact
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-## Technical Specifications [optional]
-### Model Architecture and Objective
-[More Information Needed]
-### Compute Infrastructure
-[More Information Needed]
-#### Hardware
-[More Information Needed]
-#### Software
-[More Information Needed]
-## Citation [optional]
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-**BibTeX:**
-[More Information Needed]
-**APA:**
-[More Information Needed]
-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-[More Information Needed]
-## More Information [optional]
-[More Information Needed]
-## Model Card Authors [optional]
-[More Information Needed]
-## Model Card Contact
-[More Information Needed]

 ---
+license: llama3.2
+base_model: meta-llama/Meta-Llama-3.2-3B
+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-3.2-3B-Instruct-Spatial-SQL-1.1, is an 3B, 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 five primary geographic functions released in version 1.1.
+**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 |
+</br>
+| Function  |  Question Input  | Geo Input 1             |  Geo Input 2            |               SQL Execution Output             |
+|:---------:|:----------------:|:-----------------------:|:-----------------------:|:-----------------------------------------------|
+| Distance  | Distance question| Point, Line, or Polygon | Point, Line, or Polygon | Number - Distance between geometries 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>
+DISTANCE
+<p></p>
+\### INPUT: How far apart is the point and line? : 'Point(-109.87549823 38.60574249)' 'LineString(-109.24324628 38.76349931, -109.4821773 38.6875815)'
+<p></p>
+\### Response: SELECT ST_Distance(gg1, gg2) As distance FROM (select 'Point(-109.87549823 38.60574249)' :: geography gg1, 'LineString(-109.24324628 38.76349931, -109.4821773 38.6875815)' :: geography gg2) 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?
+<p></p>
+DISTANCE
+<p></p>
+The distance between the polygon and the line is?
+<p></p>
+What is the distance between the points?
+<p></p>
+How far apart are the two lines?
+### llama.cpp / Hyperparameter Recommendations For Inference
+max context ~ 8,000 or lower
+<p></p>
+top k ~ 100
+<p></p>
+temp ~ .4-.5 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: 2e-4
+- train_batch_size: 10
+- eval_batch_size: 3
+- distributed_type: multi-GPU
+- num_devices: 2
+- optimizer: Adam 8bit
+- lr_scheduler_type: linear
+- num_epochs: 5
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.3788        |   5    |  10  |  	1.3543        |
+| 0.8504        |   5    |  20  |   0.8671        |
+| 0.5990        |   5    |  30  |   0.6501        |
+| 0.5836        |   5    |  40  |  	0.5885        |
+| 0.5713        |   5    |  50  |   0.5607        |
+| 0.5481        |   5    |  60  |   0.5434        |
+| 0.5221        |   5    |  70  |   0.5342        |
+| 0.4983        |   5    |  80  |  	0.5259        |
+| 0.4914        |   5    |  90  |   0.5219        |
+| 0.4754        |   5    |  100 |   0.5205        |
+### Framework versions
+- Transformers 4.45.1
+- Pytorch 2.4.1
+- peft 0.13.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0