dump_model_weights_and_reload.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import numpy as np\n",
    "from LoraHelpers import LoraModule, convert_model_to_lora_model, change_lora_alpha, dump_lora_weights, load_lora_weights\n",
    "import pickle\n",
    "\n",
    "model_path = \"./llama-3.2-1b-inst\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "tokenizer = AutoTokenizer.from_pretrained(model_path)\n",
    "model = AutoModelForCausalLM.from_pretrained(model_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# with open(\"lora_model.pkl\", 'rb') as f:\n",
    "#     tmp_model = pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "load_lora_weights(model, \"lora_weights.pkl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "change_lora_alpha(model, 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n",
      "Setting `pad_token_id` to `eos_token_id`:None for open-end generation.\n",
      "The attention mask is not set and cannot be inferred from input because pad token is same as eos token. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n",
      "Starting from v4.46, the `logits` model output will have the same type as the model (except at train time, where it will always be FP32)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<|begin_of_text|>Don't cry because its over, smile because it happened | tags:', 'crying', 'smile', 'smiling']<|eot_id|>\n"
     ]
    }
   ],
   "source": [
    "s = tokenizer(\"Don't cry because its over, smile because it happened | tags:\", return_tensors='pt')['input_ids']\n",
    "a = model.generate(s, max_new_tokens=200)\n",
    "print(\"\".join([tokenizer.decode(token) for token in a[0]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n",
      "Setting `pad_token_id` to `eos_token_id`:None for open-end generation.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<|begin_of_text|>Playing the bass guitar is fun | tags: bass guitar', 'play', 'rocking', 'sarcasm']<|eot_id|>\n"
     ]
    }
   ],
   "source": [
    "s = tokenizer(\"Playing the bass guitar is fun | tags:\", return_tensors='pt')['input_ids']\n",
    "a = model.generate(s, max_new_tokens=20)\n",
    "print(\"\".join([tokenizer.decode(token) for token in a[0]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "change_lora_alpha(model, 0.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n",
      "Setting `pad_token_id` to `eos_token_id`:None for open-end generation.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<|begin_of_text|>Playing the bass guitar is fun | tags: bass, music, guitar, playing, fun\n",
      "\n",
      "I've always been fascinated by the bass guitar.\n"
     ]
    }
   ],
   "source": [
    "s = tokenizer(\"Playing the bass guitar is fun | tags:\", return_tensors='pt')['input_ids']\n",
    "a = model.generate(s, max_new_tokens=20)\n",
    "print(\"\".join([tokenizer.decode(token) for token in a[0]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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