notebook.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip -q install -U transformers smirk\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from transformers import AutoModel\nfrom smirk import SmirkTokenizerFast\n\n# Load the model\nmodel = AutoModel.from_pretrained(\n    'mist-models/mist-28M-solvent-properties',\n    trust_remote_code=True\n)\n\n# Make predictions\nsmiles_batch = [\n    \"CCO\",           # Ethanol\n    \"CC(=O)O\",       # Acetic acid\n    \"C1=CC=CC=C1\"       # Benzene\n]\nresults = model.predict(smiles_batch)\nresults\n"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "provenance": []
  },
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3"
  },
  "language_info": {
   "name": "python"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}