This model is delivered as a Docker image and takes a CSV file as input and writes the results as CSV file. Sample_entry.zip file in this page provides a ready to use sample file to test the model.
Getting the model
We provide this model as a Docker image. To retrieve and run the model, install Docker Engine.
Then get the image :
docker pull abelalonso1305/tech-inceptive-models:ai4czc_1
Running the model
To provide the CSV file you are going to use, you will mount the folder containing the input file on the /data folder of the image. Then the docker image will run and create an output file on the same folder.
If your input file is named sample_entry.csv and it is located in your current directory and you want to save the predictions on output.csv, run :
docker run --rm -v "$(pwd)":/data abelalonso1305/tech-inceptive-models:ai4czc_1 -i /data/sample_entry.csv -o /data/output.csv
Is is possible to specify some aspects of the provided CSV.
-h,--help Displays this help message.
-i,--input-file Input CSV file path.
-o,--output-file Output file path to print the output CSV.
-id,--id CSV ID column name, default is _id.
-s,--separator CSV column separator, default is ','.
-ec,--escape-char CSV escape character, default is '"'.
If you want to run with a CSV in the current directory, specify the that the CSV separator will be a ";" and the id column will be "id", then run :
docker run --rm -v "$(pwd)":/data inceptive/modelcli:1 -i /data/input.csv -o /data/output.csv --id id -s ;
About this model
This model was done in the context of AI4CZC project.
This ML model is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under I-NERGY grant agreement No 101016508.