{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8698971f",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "import os\n",
    "if \"COLAB_\" not in \"\".join(os.environ.keys()):\n",
    "    !pip install unsloth\n",
    "else:\n",
    "    # Do this only in Colab notebooks! Otherwise use pip install unsloth\n",
    "    !pip install --no-deps bitsandbytes accelerate xformers==0.0.29.post3 peft trl==0.15.2 triton cut_cross_entropy unsloth_zoo\n",
    "    !pip install sentencepiece protobuf datasets huggingface_hub hf_transfer\n",
    "    !pip install --no-deps unsloth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "60b09021",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "\u001b[?25hINFO: This is taking longer than usual. You might need to provide the dependency resolver with stricter constraints to reduce runtime. See https://pip.pypa.io/warnings/backtracking for guidance. If you want to abort this run, press Ctrl + C.\n",
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      "\u001b[?25h\u001b[31mERROR: Operation cancelled by user\u001b[0m\u001b[31m\n",
      "\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "^C\n"
     ]
    }
   ],
   "source": [
    "!pip install unsloth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b07c68dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting torch\n",
      "  Using cached torch-2.7.0-cp310-cp310-manylinux_2_28_x86_64.whl (865.2 MB)\n",
      "Collecting nvidia-cufft-cu12==11.3.0.4\n",
      "  Using cached nvidia_cufft_cu12-11.3.0.4-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (200.2 MB)\n",
      "Requirement already satisfied: filelock in /home/darth/.pyenv/versions/3.10.12/envs/unsloth/lib/python3.10/site-packages (from torch) (3.18.0)\n",
      "Collecting nvidia-cuda-runtime-cu12==12.6.77\n",
      "  Using cached nvidia_cuda_runtime_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (897 kB)\n",
      "Collecting nvidia-cudnn-cu12==9.5.1.17\n",
      "  Using cached nvidia_cudnn_cu12-9.5.1.17-py3-none-manylinux_2_28_x86_64.whl (571.0 MB)\n",
      "Collecting jinja2\n",
      "  Using cached jinja2-3.1.6-py3-none-any.whl (134 kB)\n",
      "Collecting nvidia-cublas-cu12==12.6.4.1\n",
      "  Using cached nvidia_cublas_cu12-12.6.4.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (393.1 MB)\n",
      "Requirement already satisfied: typing-extensions>=4.10.0 in /home/darth/.pyenv/versions/3.10.12/envs/unsloth/lib/python3.10/site-packages (from torch) (4.13.2)\n",
      "Requirement already satisfied: triton==3.3.0 in /home/darth/.pyenv/versions/3.10.12/envs/unsloth/lib/python3.10/site-packages (from torch) (3.3.0)\n",
      "Collecting nvidia-cufile-cu12==1.11.1.6\n",
      "  Using cached nvidia_cufile_cu12-1.11.1.6-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (1.1 MB)\n",
      "Collecting nvidia-cusparse-cu12==12.5.4.2\n",
      "  Using cached nvidia_cusparse_cu12-12.5.4.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (216.6 MB)\n",
      "Collecting nvidia-nccl-cu12==2.26.2\n",
      "  Using cached nvidia_nccl_cu12-2.26.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (201.3 MB)\n",
      "Collecting nvidia-nvjitlink-cu12==12.6.85\n",
      "  Using cached nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl (19.7 MB)\n",
      "Collecting nvidia-curand-cu12==10.3.7.77\n",
      "  Using cached nvidia_curand_cu12-10.3.7.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (56.3 MB)\n",
      "Collecting nvidia-cusparselt-cu12==0.6.3\n",
      "  Using cached nvidia_cusparselt_cu12-0.6.3-py3-none-manylinux2014_x86_64.whl (156.8 MB)\n",
      "Collecting nvidia-nvtx-cu12==12.6.77\n",
      "  Using cached nvidia_nvtx_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (89 kB)\n",
      "Collecting nvidia-cuda-cupti-cu12==12.6.80\n",
      "  Using cached nvidia_cuda_cupti_cu12-12.6.80-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (8.9 MB)\n",
      "Collecting networkx\n",
      "  Using cached networkx-3.4.2-py3-none-any.whl (1.7 MB)\n",
      "Collecting sympy>=1.13.3\n",
      "  Using cached sympy-1.14.0-py3-none-any.whl (6.3 MB)\n",
      "Requirement already satisfied: fsspec in /home/darth/.pyenv/versions/3.10.12/envs/unsloth/lib/python3.10/site-packages (from torch) (2024.12.0)\n",
      "Collecting nvidia-cuda-nvrtc-cu12==12.6.77\n",
      "  Using cached nvidia_cuda_nvrtc_cu12-12.6.77-py3-none-manylinux2014_x86_64.whl (23.7 MB)\n",
      "Collecting nvidia-cusolver-cu12==11.7.1.2\n",
      "  Using cached nvidia_cusolver_cu12-11.7.1.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (158.2 MB)\n",
      "Requirement already satisfied: setuptools>=40.8.0 in /home/darth/.pyenv/versions/3.10.12/envs/unsloth/lib/python3.10/site-packages (from triton==3.3.0->torch) (65.5.0)\n",
      "Collecting mpmath<1.4,>=1.1.0\n",
      "  Downloading mpmath-1.3.0-py3-none-any.whl (536 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m536.2/536.2 kB\u001b[0m \u001b[31m10.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n",
      "\u001b[?25hCollecting MarkupSafe>=2.0\n",
      "  Downloading MarkupSafe-3.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (20 kB)\n",
      "Installing collected packages: nvidia-cusparselt-cu12, mpmath, sympy, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufile-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, networkx, MarkupSafe, nvidia-cusparse-cu12, nvidia-cufft-cu12, nvidia-cudnn-cu12, jinja2, nvidia-cusolver-cu12, torch\n",
      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "unsloth 2025.4.1 requires diffusers, which is not installed.\n",
      "unsloth 2025.4.1 requires psutil, which is not installed.\n",
      "unsloth 2025.4.1 requires torchvision, which is not installed.\n",
      "unsloth 2025.4.1 requires transformers!=4.47.0,>=4.46.1, which is not installed.\n",
      "unsloth 2025.4.1 requires tyro, which is not installed.\n",
      "unsloth 2025.4.1 requires wheel>=0.42.0, which is not installed.\n",
      "unsloth-zoo 2025.4.1 requires pillow, which is not installed.\n",
      "unsloth-zoo 2025.4.1 requires psutil, which is not installed.\n",
      "unsloth-zoo 2025.4.1 requires regex, which is not installed.\n",
      "unsloth-zoo 2025.4.1 requires transformers!=4.47.0,>=4.46.1, which is not installed.\n",
      "unsloth-zoo 2025.4.1 requires tyro, which is not installed.\n",
      "unsloth-zoo 2025.4.1 requires wheel>=0.42.0, which is not installed.\n",
      "peft 0.15.2 requires psutil, which is not installed.\n",
      "peft 0.15.2 requires safetensors, which is not installed.\n",
      "peft 0.15.2 requires transformers, which is not installed.\n",
      "accelerate 1.6.0 requires psutil, which is not installed.\n",
      "accelerate 1.6.0 requires safetensors>=0.4.3, which is not installed.\n",
      "xformers 0.0.29.post3 requires torch==2.6.0, but you have torch 2.7.0 which is incompatible.\n",
      "unsloth 2025.4.1 requires protobuf<4.0.0, but you have protobuf 6.30.2 which is incompatible.\n",
      "unsloth-zoo 2025.4.1 requires protobuf<4.0.0, but you have protobuf 6.30.2 which is incompatible.\u001b[0m\u001b[31m\n",
      "\u001b[0mSuccessfully installed MarkupSafe-3.0.2 jinja2-3.1.6 mpmath-1.3.0 networkx-3.4.2 nvidia-cublas-cu12-12.6.4.1 nvidia-cuda-cupti-cu12-12.6.80 nvidia-cuda-nvrtc-cu12-12.6.77 nvidia-cuda-runtime-cu12-12.6.77 nvidia-cudnn-cu12-9.5.1.17 nvidia-cufft-cu12-11.3.0.4 nvidia-cufile-cu12-1.11.1.6 nvidia-curand-cu12-10.3.7.77 nvidia-cusolver-cu12-11.7.1.2 nvidia-cusparse-cu12-12.5.4.2 nvidia-cusparselt-cu12-0.6.3 nvidia-nccl-cu12-2.26.2 nvidia-nvjitlink-cu12-12.6.85 nvidia-nvtx-cu12-12.6.77 sympy-1.14.0 torch-2.7.0\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install torch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8b3433cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_21635/2994791960.py:1: UserWarning: WARNING: Unsloth should be imported before trl, transformers to ensure all optimizations are applied. Your code may run slower or encounter memory issues without these optimizations.\n",
      "\n",
      "Please restructure your imports with 'import unsloth' at the top of your file.\n",
      "  from unsloth import FastLanguageModel\n",
      "WARNING[XFORMERS]: xFormers can't load C++/CUDA extensions. xFormers was built for:\n",
      "    PyTorch 2.6.0+cu124 with CUDA 1204 (you have 2.7.0+cu126)\n",
      "    Python  3.10.16 (you have 3.10.12)\n",
      "  Please reinstall xformers (see https://github.com/facebookresearch/xformers#installing-xformers)\n",
      "  Memory-efficient attention, SwiGLU, sparse and more won't be available.\n",
      "  Set XFORMERS_MORE_DETAILS=1 for more details\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unsloth: Failed to patch SmolVLMForConditionalGeneration forward function.\n",
      "🦥 Unsloth Zoo will now patch everything to make training faster!\n",
      "==((====))==  Unsloth 2025.4.1: Fast Llama patching. Transformers: 4.51.3.\n",
      "   \\\\   /|    NVIDIA GeForce RTX 3060. Num GPUs = 1. Max memory: 11.633 GB. Platform: Linux.\n",
      "O^O/ \\_/ \\    Torch: 2.7.0+cu126. CUDA: 8.6. CUDA Toolkit: 12.6. Triton: 3.3.0\n",
      "\\        /    Bfloat16 = TRUE. FA [Xformers = None. FA2 = False]\n",
      " \"-____-\"     Free license: http://github.com/unslothai/unsloth\n",
      "Unsloth: Fast downloading is enabled - ignore downloading bars which are red colored!\n"
     ]
    }
   ],
   "source": [
    "from unsloth import FastLanguageModel\n",
    "import torch\n",
    "max_seq_length = 2048 # Choose any! We auto support RoPE Scaling internally!\n",
    "dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+\n",
    "load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False.\n",
    "\n",
    "# 4bit pre quantized models we support for 4x faster downloading + no OOMs.\n",
    "fourbit_models = [\n",
    "    \"unsloth/Meta-Llama-3.1-8B-bnb-4bit\",      # Llama-3.1 15 trillion tokens model 2x faster!\n",
    "    \"unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit\",\n",
    "    \"unsloth/Meta-Llama-3.1-70B-bnb-4bit\",\n",
    "    \"unsloth/Meta-Llama-3.1-405B-bnb-4bit\",    # We also uploaded 4bit for 405b!\n",
    "    \"unsloth/Mistral-Nemo-Base-2407-bnb-4bit\", # New Mistral 12b 2x faster!\n",
    "    \"unsloth/Mistral-Nemo-Instruct-2407-bnb-4bit\",\n",
    "    \"unsloth/mistral-7b-v0.3-bnb-4bit\",        # Mistral v3 2x faster!\n",
    "    \"unsloth/mistral-7b-instruct-v0.3-bnb-4bit\",\n",
    "    \"unsloth/Phi-3.5-mini-instruct\",           # Phi-3.5 2x faster!\n",
    "    \"unsloth/Phi-3-medium-4k-instruct\",\n",
    "    \"unsloth/gemma-2-9b-bnb-4bit\",\n",
    "    \"unsloth/gemma-2-27b-bnb-4bit\",            # Gemma 2x faster!\n",
    "] # More models at https://huggingface.co/unsloth\n",
    "\n",
    "model, tokenizer = FastLanguageModel.from_pretrained(\n",
    "    model_name = \"unsloth/Meta-Llama-3.1-8B\",\n",
    "    max_seq_length = max_seq_length,\n",
    "    dtype = dtype,\n",
    "    load_in_4bit = load_in_4bit,\n",
    "    # token = \"hf_...\", # use one if using gated models like meta-llama/Llama-2-7b-hf\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5589b14e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Unsloth 2025.4.1 patched 32 layers with 32 QKV layers, 32 O layers and 32 MLP layers.\n"
     ]
    }
   ],
   "source": [
    "model = FastLanguageModel.get_peft_model(\n",
    "    model,\n",
    "    r = 16, # Choose any number > 0 ! Suggested 8, 16, 32, 64, 128\n",
    "    target_modules = [\"q_proj\", \"k_proj\", \"v_proj\", \"o_proj\",\n",
    "                      \"gate_proj\", \"up_proj\", \"down_proj\",],\n",
    "    lora_alpha = 16,\n",
    "    lora_dropout = 0, # Supports any, but = 0 is optimized\n",
    "    bias = \"none\",    # Supports any, but = \"none\" is optimized\n",
    "    # [NEW] \"unsloth\" uses 30% less VRAM, fits 2x larger batch sizes!\n",
    "    use_gradient_checkpointing = \"unsloth\", # True or \"unsloth\" for very long context\n",
    "    random_state = 3407,\n",
    "    use_rslora = False,  # We support rank stabilized LoRA\n",
    "    loftq_config = None, # And LoftQ\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d396cc70",
   "metadata": {},
   "outputs": [],
   "source": [
    "alpaca_prompt = \"\"\"Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n",
    "\n",
    "### Instruction:\n",
    "{}\n",
    "\n",
    "### Input:\n",
    "{}\n",
    "\n",
    "### Response:\n",
    "{}\"\"\"\n",
    "\n",
    "EOS_TOKEN = tokenizer.eos_token # Must add EOS_TOKEN\n",
    "def formatting_prompts_func(examples):\n",
    "    instructions = examples[\"instruction\"]\n",
    "    inputs       = examples[\"input\"]\n",
    "    outputs      = examples[\"output\"]\n",
    "    texts = []\n",
    "    for instruction, input, output in zip(instructions, inputs, outputs):\n",
    "        # Must add EOS_TOKEN, otherwise your generation will go on forever!\n",
    "        text = alpaca_prompt.format(instruction, input, output) + EOS_TOKEN\n",
    "        texts.append(text)\n",
    "    return { \"text\" : texts, }\n",
    "pass\n",
    "\n",
    "from datasets import load_dataset\n",
    "dataset = load_dataset(\"yahma/alpaca-cleaned\", split = \"train\")\n",
    "dataset = dataset.map(formatting_prompts_func, batched = True,)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "unsloth",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
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 },
 "nbformat": 4,
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