mytest.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "J8TTlQeqcMXh",
        "outputId": "ca5e335f-fe8b-4398-9635-5b1284405385"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting unsloth@ git+https://github.com/unslothai/unsloth.git (from unsloth[colab]@ git+https://github.com/unslothai/unsloth.git)\n",
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            "Collecting nvidia-nccl-cu12==2.18.1 (from torch>=1.10.0->accelerate>=0.34.1->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab]@ git+https://github.com/unslothai/unsloth.git)\n",
            "  Downloading nvidia_nccl_cu12-2.18.1-py3-none-manylinux1_x86_64.whl.metadata (1.8 kB)\n",
            "Collecting nvidia-nvtx-cu12==12.1.105 (from torch>=1.10.0->accelerate>=0.34.1->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab]@ git+https://github.com/unslothai/unsloth.git)\n",
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            "Collecting triton (from unsloth-zoo>=2024.11.1->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab]@ git+https://github.com/unslothai/unsloth.git)\n",
            "  Downloading triton-2.1.0-0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.3 kB)\n",
            "Requirement already satisfied: nvidia-nvjitlink-cu12 in /usr/local/lib/python3.10/dist-packages (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.10.0->accelerate>=0.34.1->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab]@ git+https://github.com/unslothai/unsloth.git) (12.6.77)\n",
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            "\u001b[?25hDownloading xxhash-3.5.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (194 kB)\n",
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            "\u001b[?25hBuilding wheels for collected packages: unsloth\n",
            "  Building wheel for unsloth (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for unsloth: filename=unsloth-2024.11.7-py3-none-any.whl size=163138 sha256=999a200c8d6ac7564fc5b4ef4a392e64a7f6f03311ab24393596a1d365c172a7\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-5m3oif7o/wheels/ed/d4/e9/76fb290ee3df0a5fc21ce5c2c788e29e9607a2353d8342fd0d\n",
            "Successfully built unsloth\n",
            "Installing collected packages: xxhash, unsloth, triton, shtab, protobuf, nvidia-nvtx-cu12, nvidia-nccl-cu12, nvidia-cusparse-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, jedi, hf-transfer, fsspec, dill, nvidia-cusolver-cu12, nvidia-cudnn-cu12, multiprocess, tyro, torch, xformers, bitsandbytes, datasets, trl, unsloth-zoo\n",
            "  Attempting uninstall: protobuf\n",
            "    Found existing installation: protobuf 4.25.5\n",
            "    Uninstalling protobuf-4.25.5:\n",
            "      Successfully uninstalled protobuf-4.25.5\n",
            "  Attempting uninstall: nvidia-nccl-cu12\n",
            "    Found existing installation: nvidia-nccl-cu12 2.23.4\n",
            "    Uninstalling nvidia-nccl-cu12-2.23.4:\n",
            "      Successfully uninstalled nvidia-nccl-cu12-2.23.4\n",
            "  Attempting uninstall: nvidia-cusparse-cu12\n",
            "    Found existing installation: nvidia-cusparse-cu12 12.5.4.2\n",
            "    Uninstalling nvidia-cusparse-cu12-12.5.4.2:\n",
            "      Successfully uninstalled nvidia-cusparse-cu12-12.5.4.2\n",
            "  Attempting uninstall: nvidia-curand-cu12\n",
            "    Found existing installation: nvidia-curand-cu12 10.3.7.77\n",
            "    Uninstalling nvidia-curand-cu12-10.3.7.77:\n",
            "      Successfully uninstalled nvidia-curand-cu12-10.3.7.77\n",
            "  Attempting uninstall: nvidia-cufft-cu12\n",
            "    Found existing installation: nvidia-cufft-cu12 11.3.0.4\n",
            "    Uninstalling nvidia-cufft-cu12-11.3.0.4:\n",
            "      Successfully uninstalled nvidia-cufft-cu12-11.3.0.4\n",
            "  Attempting uninstall: nvidia-cuda-runtime-cu12\n",
            "    Found existing installation: nvidia-cuda-runtime-cu12 12.6.77\n",
            "    Uninstalling nvidia-cuda-runtime-cu12-12.6.77:\n",
            "      Successfully uninstalled nvidia-cuda-runtime-cu12-12.6.77\n",
            "  Attempting uninstall: nvidia-cuda-cupti-cu12\n",
            "    Found existing installation: nvidia-cuda-cupti-cu12 12.6.80\n",
            "    Uninstalling nvidia-cuda-cupti-cu12-12.6.80:\n",
            "      Successfully uninstalled nvidia-cuda-cupti-cu12-12.6.80\n",
            "  Attempting uninstall: nvidia-cublas-cu12\n",
            "    Found existing installation: nvidia-cublas-cu12 12.6.3.3\n",
            "    Uninstalling nvidia-cublas-cu12-12.6.3.3:\n",
            "      Successfully uninstalled nvidia-cublas-cu12-12.6.3.3\n",
            "  Attempting uninstall: fsspec\n",
            "    Found existing installation: fsspec 2024.10.0\n",
            "    Uninstalling fsspec-2024.10.0:\n",
            "      Successfully uninstalled fsspec-2024.10.0\n",
            "  Attempting uninstall: nvidia-cusolver-cu12\n",
            "    Found existing installation: nvidia-cusolver-cu12 11.7.1.2\n",
            "    Uninstalling nvidia-cusolver-cu12-11.7.1.2:\n",
            "      Successfully uninstalled nvidia-cusolver-cu12-11.7.1.2\n",
            "  Attempting uninstall: nvidia-cudnn-cu12\n",
            "    Found existing installation: nvidia-cudnn-cu12 9.5.1.17\n",
            "    Uninstalling nvidia-cudnn-cu12-9.5.1.17:\n",
            "      Successfully uninstalled nvidia-cudnn-cu12-9.5.1.17\n",
            "  Attempting uninstall: torch\n",
            "    Found existing installation: torch 2.5.1+cu121\n",
            "    Uninstalling torch-2.5.1+cu121:\n",
            "      Successfully uninstalled torch-2.5.1+cu121\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",
            "gcsfs 2024.10.0 requires fsspec==2024.10.0, but you have fsspec 2024.9.0 which is incompatible.\n",
            "grpcio-status 1.62.3 requires protobuf>=4.21.6, but you have protobuf 3.20.3 which is incompatible.\n",
            "torchaudio 2.5.1+cu121 requires torch==2.5.1, but you have torch 2.1.0 which is incompatible.\n",
            "torchvision 0.20.1+cu121 requires torch==2.5.1, but you have torch 2.1.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed bitsandbytes-0.44.1 datasets-3.1.0 dill-0.3.8 fsspec-2024.9.0 hf-transfer-0.1.8 jedi-0.19.2 multiprocess-0.70.16 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.18.1 nvidia-nvtx-cu12-12.1.105 protobuf-3.20.3 shtab-1.7.1 torch-2.1.0 triton-2.1.0 trl-0.12.1 tyro-0.9.1 unsloth-2024.11.7 unsloth-zoo-2024.11.5 xformers-0.0.22.post7 xxhash-3.5.0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "google"
                ]
              },
              "id": "ca19c9bcbd4f4044856be4b5b7a72bfd"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "pip install huggingface_hub ipython \"unsloth[colab] @ git+https://github.com/unslothai/unsloth.git\" \"unsloth[conda] @ git+https://github.com/unslothai/unsloth.git\""
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%env HF_TOKEN=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"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-CEhXTyIeMAj",
        "outputId": "898aaa1b-6b47-4fc9-9100-6b91180910b0"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "env: HF_TOKEN=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\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 1. Importing and configurations\n",
        "import os\n",
        "from unsloth import FastLanguageModel\n",
        "import torch\n",
        "from trl import SFTTrainer\n",
        "from transformers import TrainingArguments\n",
        "from datasets import load_dataset\n",
        "\n",
        "max_seq_length = 2048\n",
        "url = \"https://huggingface.co/datasets/mausombi/parle_g\"\n",
        "dataset = load_dataset(\"json\", data_files = {\"train\" : url}, split = \"train\")\n",
        "\n",
        "# 2. Load Mistral model\n",
        "model, tokenizer = FastLanguageModel.from_pretrained(\n",
        "    model_name = \"unsloth/mistral-7b-bnb-4bit\",\n",
        "    max_seq_length = max_seq_length,\n",
        "    dtype = None,\n",
        "    load_in_4bit = True,\n",
        ")\n",
        "\n",
        "# 3 Before training\n",
        "def generate_text(text):\n",
        "    inputs = tokenizer(text, return_tensors=\"pt\").to(\"cuda:0\")\n",
        "    outputs = model.generate(**inputs, max_new_tokens=20)\n",
        "    print(tokenizer.decode(outputs[0], skip_special_tokens=True))\n",
        "print(\"Before training\\n\")\n",
        "generate_text(\"List the top 5 most popular movies of all time.\")\n",
        "\n",
        "# 4. Do model patching and add fast LoRA weights and training\n",
        "model = FastLanguageModel.get_peft_model(\n",
        "    model,\n",
        "    r = 16,\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",
        "    use_gradient_checkpointing = True,\n",
        "    random_state = 3407,\n",
        "    max_seq_length = max_seq_length,\n",
        "    use_rslora = False,  # Rank stabilized LoRA\n",
        "    loftq_config = None, # LoftQ\n",
        ")\n",
        "\n",
        "trainer = SFTTrainer(\n",
        "    model = model,\n",
        "    train_dataset = dataset,\n",
        "    dataset_text_field = \"text\",\n",
        "    max_seq_length = max_seq_length,\n",
        "    tokenizer = tokenizer,\n",
        "    args = TrainingArguments(\n",
        "        per_device_train_batch_size = 2,\n",
        "        gradient_accumulation_steps = 4,\n",
        "        warmup_steps = 10,\n",
        "        max_steps = 60,\n",
        "        fp16 = not torch.cuda.is_bf16_supported(),\n",
        "        bf16 = torch.cuda.is_bf16_supported(),\n",
        "        logging_steps = 1,\n",
        "        output_dir = \"outputs\",\n",
        "        optim = \"adamw_8bit\",\n",
        "        seed = 3407,\n",
        "    ),\n",
        ")\n",
        "trainer.train()\n",
        "\n",
        "print(\"\\n ######## \\nAfter training\\n\")\n",
        "generate_text(\"List the top 5 most popular movies of all time.\")\n",
        "\n",
        "# 5. Save and push to Hub\n",
        "model.save_pretrained(\"lora_model\")\n",
        "model.save_pretrained_merged(\"outputs\", tokenizer, save_method = \"merged_16bit\",)\n",
        "model.push_to_hub_merged(\"praison/mistral-7b-oig-unsloth-merged\", tokenizer, save_method = \"merged_16bit\", token = os.environ.get(\"HF_TOKEN\"))\n",
        "model.push_to_hub(\"praison/mistral-7b-oig-unsloth\", tokenizer, save_method = \"lora\", token = os.environ.get(\"HF_TOKEN\"))"
      ],
      "metadata": {
        "id": "Vva2h0ODeMP-"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}