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2024-08-24 14:47:21 +05:30

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{
"cells": [
{
"metadata": {},
"cell_type": "code",
"outputs": [],
"execution_count": null,
"source": "!pip install labml-nn",
"id": "c5ed37230628ee76"
},
{
"metadata": {},
"cell_type": "code",
"source": [
"from labml_nn.lora.experiment import Trainer\n",
"from labml import experiment"
],
"id": "1b9da2e59ffce5d5",
"outputs": [],
"execution_count": null
},
{
"cell_type": "code",
"id": "initial_id",
"metadata": {
"collapsed": true
},
"source": "experiment.create(name=\"lora_gpt2\")",
"outputs": [],
"execution_count": null
},
{
"metadata": {},
"cell_type": "code",
"source": "trainer = Trainer()",
"id": "31c9bc08eca2592",
"outputs": [],
"execution_count": null
},
{
"metadata": {},
"cell_type": "code",
"source": "experiment.configs(trainer)",
"id": "fb6ce74326558948",
"outputs": [],
"execution_count": null
},
{
"metadata": {},
"cell_type": "code",
"source": "trainer.initialize()",
"id": "1456cfab47dee3b",
"outputs": [],
"execution_count": null
},
{
"metadata": {},
"cell_type": "code",
"source": [
"with experiment.start():\n",
" trainer.run()"
],
"id": "3fe4068fd2df9094",
"outputs": [],
"execution_count": null
},
{
"metadata": {},
"cell_type": "code",
"source": "",
"id": "d3c3c723ebbe854a",
"outputs": [],
"execution_count": null
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (ml)",
"language": "python",
"name": "ml"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 5
}