Simple/Basic tutorial

Hello,

Perhaps a very simple question despite having dug into the graphormer documentation: Assume given a csv training file containing tens of thousands of SMILES and their corresponding properties, say just 2 properties. For example the training .csv file will look like

SMILES, Property 1, Property 2
SMILE1, some_number11, some_number21 
SMILE2, some_number12, some_number22
SMILE3, some_number13, some_number23
...

At this point, I only know that I will have to invoke the command fairseq-train --user-dir path/to/graphormer with a lot of settings from the fairseq page (https://fairseq.readthedocs.io/en/latest/command_line_tools.html#fairseq-train) and Graphormer's documentation. On the website, I could just roughly make sense of the oc20 (Train a New Model) example that uses lmdb files. So for the very simple case mentioned above (1 huge training csv file, and a separate test csv file), how do I go about using Graphormer?

I would appreciate if someone could give some pointers or direct me to the correct destination in the documentation that I might have overlooked.

Thank you.

Best,
Jacey

Start with the existing OC20 “Train a New Model” example and the fairseq-train command-line documentation linked in the issue. Determine whether the project already supports CSV input for SMILES and two properties, then document the required workflow for separate training and test CSV files. Done means a newcomer can follow the documented commands without relying on LMDB examples.