alihan/llm-course
1
0
Fork 0
mirror of https://github.com/mlabonne/llm-course.git synced 2024-01-14 16:32:03 +03:00
Code Issues Packages Projects Releases Wiki Activity

updated notebook

Browse Source
This commit is contained in:
Maxime Labonne
2023-07-26 21:30:16 +01:00
parent 5726fea665
commit 01128d3d1f
1 changed files with 29 additions and 13 deletions
Download Patch File Download Diff File Expand all files Collapse all files

42
Fine_tune_Llama_2_in_Google_Colab.ipynb
View File

@@ -6,7 +6,7 @@
"provenance": [],
"machine_shape": "hm",
"gpuType": "V100",
"authorship_tag": "ABX9TyPNl/WKBYXOzuJCP/puYm6d",
"authorship_tag": "ABX9TyMElK+4/0JPkM9Cs0WQVGXA",
"include_colab_link": true
},
"kernelspec": {
@@ -37,7 +37,7 @@
"\n",
"❤️ Created by [@maximelabonne](), based on Younes Belkada's [GitHub Gist](https://gist.github.com/younesbelkada/9f7f75c94bdc1981c8ca5cc937d4a4da).\n",
"\n",
"This notebook runs on a T4 GPU with high RAM. (Last update: 23 Jul 2023)\n"
"This notebook runs on a T4 GPU with high RAM. (Last update: 26 Jul 2023)\n"
],
"metadata": {
"id": "OSHlAbqzDFDq"
@@ -88,19 +88,19 @@
"dataset_name = \"mlabonne/guanaco-llama2-1k\"\n",
"\n",
"# Fine-tuned model name\n",
"new_model = \"llama-2-7b-guanaco\"\n",
"new_model = \"llama-2-7b-miniguanaco\"\n",
"\n",
"################################################################################\n",
"# QLoRA parameters\n",
"################################################################################\n",
"\n",
"# Lora attention dimension\n",
"# LoRA attention dimension\n",
"lora_r = 64\n",
"\n",
"# Alpha parameter for Lora scaling\n",
"# Alpha parameter for LoRA scaling\n",
"lora_alpha = 16\n",
"\n",
"# Dropout probability for Lora layers\n",
"# Dropout probability for LoRA layers\n",
"lora_dropout = 0.1\n",
"\n",
"################################################################################\n",
@@ -140,7 +140,7 @@
"per_device_eval_batch_size = 4\n",
"\n",
"# Number of update steps to accumulate the gradients for\n",
"gradient_accumulation_steps = 1\n",
"gradient_accumulation_steps = 2\n",
"\n",
"# Enable gradient checkpointing\n",
"gradient_checkpointing = True\n",
@@ -228,6 +228,11 @@
"model.config.use_cache = False\n",
"model.config.pretraining_tp = 1\n",
"\n",
"# Load LLaMA tokenizer\n",
"tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)\n",
"tokenizer.pad_token = tokenizer.eos_token\n",
"tokenizer.padding_side = \"right\" # Fix weird overflow issue with fp16 training\n",
"\n",
"# Load LoRA configuration\n",
"peft_config = LoraConfig(\n",
" lora_alpha=lora_alpha,\n",
@@ -237,11 +242,6 @@
" task_type=\"CAUSAL_LM\",\n",
")\n",
"\n",
"# Load LLaMA tokenizer\n",
"tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)\n",
"tokenizer.pad_token = tokenizer.eos_token\n",
"tokenizer.padding_side = \"right\" # Fix weird overflow issue with fp16 training\n",
"\n",
"# Set training parameters\n",
"training_arguments = TrainingArguments(\n",
" output_dir=output_dir,\n",
@@ -290,9 +290,25 @@
{
"cell_type": "code",
"source": [
"%load_ext tensorboard\n",
"%tensorboard --logdir results/runs"
],
"metadata": {
"id": "crj9svNe4hU5"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# Ignore warnings\n",
"logging.set_verbosity(logging.CRITICAL)\n",
"\n",
"# Run text generation pipeline with our next model\n",
"prompt = \"What is a large language model?\"\n",
"pipe = pipeline(task=\"text-generation\", model=model, tokenizer=tokenizer, max_length=200)\n",
"result = pipe(\"Tell me a joke\")\n",
"result = pipe(f\"<s>[INST] {prompt} [/INST]\")\n",
"print(result[0]['generated_text'])"
],
"metadata": {