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nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m99.1/99.1 kB\u001b[0m \u001b[31m12.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: triton==2.2.0 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchvision) (2.2.0)\n", "Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch==2.2.1->torchvision)\n", " Downloading nvidia_nvjitlink_cu12-12.4.99-py3-none-manylinux2014_x86_64.whl (21.1 MB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.1/21.1 MB\u001b[0m \u001b[31m56.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch==2.2.1->torchvision) (2.1.5)\n", "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch==2.2.1->torchvision) (1.3.0)\n", "Installing collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12\n", "Successfully installed 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-cu12-2.19.3 nvidia-nvjitlink-cu12-12.4.99 nvidia-nvtx-cu12-12.1.105\n", "Requirement already satisfied: torchaudio in /usr/local/lib/python3.10/dist-packages (2.2.1+cu121)\n", "Requirement already satisfied: torch==2.2.1 in /usr/local/lib/python3.10/dist-packages (from torchaudio) (2.2.1+cu121)\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (3.13.1)\n", "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (4.10.0)\n", "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (1.12)\n", "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (3.2.1)\n", "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (3.1.3)\n", "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (2023.6.0)\n", "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (12.1.105)\n", "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (12.1.105)\n", "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (12.1.105)\n", "Requirement already satisfied: nvidia-cudnn-cu12==8.9.2.26 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (8.9.2.26)\n", "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (12.1.3.1)\n", "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (11.0.2.54)\n", "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (10.3.2.106)\n", "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (11.4.5.107)\n", "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (12.1.0.106)\n", "Requirement already satisfied: nvidia-nccl-cu12==2.19.3 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (2.19.3)\n", "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (12.1.105)\n", "Requirement already satisfied: triton==2.2.0 in /usr/local/lib/python3.10/dist-packages (from torch==2.2.1->torchaudio) (2.2.0)\n", "Requirement already satisfied: nvidia-nvjitlink-cu12 in /usr/local/lib/python3.10/dist-packages (from nvidia-cusolver-cu12==11.4.5.107->torch==2.2.1->torchaudio) (12.4.99)\n", "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch==2.2.1->torchaudio) (2.1.5)\n", "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch==2.2.1->torchaudio) (1.3.0)\n" ] } ] }, { "cell_type": "code", "source": [ "!pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121" ], "metadata": { "execution": { "iopub.status.busy": "2024-03-19T20:02:37.931189Z", "iopub.execute_input": "2024-03-19T20:02:37.931653Z", "iopub.status.idle": "2024-03-19T20:02:50.038811Z", "shell.execute_reply.started": "2024-03-19T20:02:37.931618Z", "shell.execute_reply": "2024-03-19T20:02:50.037731Z" }, "trusted": true, "colab": { "base_uri": "https://localhost:8080/" }, "id": "O4OyG3Hf0sZ2", "outputId": "652cbe7c-4624-4a84-fc19-606e7f37f186" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Looking in indexes: https://download.pytorch.org/whl/cu121\n", "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (2.2.1+cu121)\n", "Requirement already satisfied: torchvision in /usr/local/lib/python3.10/dist-packages (0.17.1+cu121)\n", "Requirement already satisfied: torchaudio in /usr/local/lib/python3.10/dist-packages (2.2.1+cu121)\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch) (3.13.1)\n", "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from torch) (4.10.0)\n", "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch) (1.12)\n", "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch) (3.2.1)\n", "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch) (3.1.3)\n", "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch) (2023.6.0)\n", "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch) (12.1.105)\n", "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch) (12.1.105)\n", "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch) (12.1.105)\n", "Requirement already satisfied: nvidia-cudnn-cu12==8.9.2.26 in /usr/local/lib/python3.10/dist-packages (from torch) (8.9.2.26)\n", "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /usr/local/lib/python3.10/dist-packages (from torch) (12.1.3.1)\n", "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /usr/local/lib/python3.10/dist-packages (from torch) (11.0.2.54)\n", "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /usr/local/lib/python3.10/dist-packages (from torch) (10.3.2.106)\n", "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /usr/local/lib/python3.10/dist-packages (from torch) (11.4.5.107)\n", "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /usr/local/lib/python3.10/dist-packages (from torch) (12.1.0.106)\n", "Requirement already satisfied: nvidia-nccl-cu12==2.19.3 in /usr/local/lib/python3.10/dist-packages (from torch) (2.19.3)\n", "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch) (12.1.105)\n", "Requirement already satisfied: triton==2.2.0 in /usr/local/lib/python3.10/dist-packages (from torch) (2.2.0)\n", "Requirement already satisfied: nvidia-nvjitlink-cu12 in /usr/local/lib/python3.10/dist-packages (from nvidia-cusolver-cu12==11.4.5.107->torch) (12.4.99)\n", "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from torchvision) (1.25.2)\n", "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.10/dist-packages (from torchvision) (9.4.0)\n", "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch) (2.1.5)\n", "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch) (1.3.0)\n" ] } ] }, { "cell_type": "code", "source": [ "!git clone https://github.com/bigcode-project/starcoder2.git" ], "metadata": { "execution": { "iopub.status.busy": "2024-03-19T20:02:50.040282Z", "iopub.execute_input": "2024-03-19T20:02:50.040611Z", "iopub.status.idle": "2024-03-19T20:02:51.596094Z", "shell.execute_reply.started": "2024-03-19T20:02:50.040584Z", "shell.execute_reply": "2024-03-19T20:02:51.595169Z" }, "trusted": true, "colab": { "base_uri": "https://localhost:8080/" }, "id": "IVmVDux90sZ2", "outputId": "18615f26-4591-4661-8c26-a71ae3baf0a9" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Cloning into 'starcoder2'...\n", "remote: Enumerating objects: 44, done.\u001b[K\n", "remote: Counting objects: 100% (44/44), done.\u001b[K\n", "remote: Compressing objects: 100% (41/41), done.\u001b[K\n", "remote: Total 44 (delta 19), reused 7 (delta 2), pack-reused 0\u001b[K\n", "Receiving objects: 100% (44/44), 20.97 KiB | 3.00 MiB/s, done.\n", "Resolving deltas: 100% (19/19), done.\n" ] } ] }, { "cell_type": "code", "source": [ "%cd \"starcoder2\"" ], "metadata": { "execution": { "iopub.status.busy": "2024-03-19T20:02:51.598325Z", "iopub.execute_input": "2024-03-19T20:02:51.598646Z", "iopub.status.idle": "2024-03-19T20:02:51.604661Z", "shell.execute_reply.started": "2024-03-19T20:02:51.598620Z", "shell.execute_reply": "2024-03-19T20:02:51.603748Z" }, "trusted": true, "colab": { "base_uri": "https://localhost:8080/" }, "id": "C5LY2OSP0sZ2", "outputId": "4d659936-7f47-4fab-9fc5-42ae18e9f67d" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "/content/starcoder2\n" ] } ] }, { "cell_type": "code", "source": [ "!pip install -r \"requirements.txt\"" ], "metadata": { "execution": { "iopub.status.busy": "2024-03-19T20:02:51.605843Z", "iopub.execute_input": "2024-03-19T20:02:51.606154Z", "iopub.status.idle": "2024-03-19T20:03:57.774917Z", "shell.execute_reply.started": "2024-03-19T20:02:51.606124Z", "shell.execute_reply": "2024-03-19T20:03:57.773685Z" }, "trusted": true, "colab": { "base_uri": "https://localhost:8080/" }, "id": "FsYI5dOO0sZ3", "outputId": "b8a59cca-17b6-4e52-a05c-3568c99e7f63" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Collecting git+https://github.com/huggingface/transformers.git (from -r requirements.txt (line 1))\n", " Cloning https://github.com/huggingface/transformers.git to /tmp/pip-req-build-c119vx02\n", " Running command git clone --filter=blob:none --quiet https://github.com/huggingface/transformers.git /tmp/pip-req-build-c119vx02\n", " Resolved https://github.com/huggingface/transformers.git to commit e85654f5ec485c96223ffc294038aae036d180da\n", " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", " 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gitdb<5,>=4.0.1->GitPython!=3.1.29,>=1.0.0->wandb==0.16.3->-r requirements.txt (line 7))\n", " Downloading smmap-5.0.1-py3-none-any.whl (24 kB)\n", "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich>=11.1.0->tyro>=0.5.11->trl==0.7.10->-r requirements.txt (line 6)) (3.0.0)\n", "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich>=11.1.0->tyro>=0.5.11->trl==0.7.10->-r requirements.txt (line 6)) (2.16.1)\n", "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.10.0->accelerate==0.27.1->-r requirements.txt (line 2)) (2.1.5)\n", "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.10.0->accelerate==0.27.1->-r requirements.txt (line 2)) (1.3.0)\n", "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich>=11.1.0->tyro>=0.5.11->trl==0.7.10->-r requirements.txt (line 6)) (0.1.2)\n", "Building wheels for collected packages: transformers\n", " Building wheel for transformers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", " Created wheel for transformers: filename=transformers-4.40.0.dev0-py3-none-any.whl size=8802995 sha256=cd6e5debbd346bdc641b0881aaa5ef3b1b0940b81d43afe6980bc8fa7fec8213\n", " Stored in directory: /tmp/pip-ephem-wheel-cache-t3mn2qvd/wheels/e7/9c/5b/e1a9c8007c343041e61cc484433d512ea9274272e3fcbe7c16\n", "Successfully built transformers\n", "Installing collected packages: bitsandbytes, xxhash, smmap, shtab, setproctitle, sentry-sdk, docstring-parser, docker-pycreds, dill, multiprocess, gitdb, tyro, GitPython, wandb, transformers, datasets, accelerate, trl, peft\n", " Attempting uninstall: transformers\n", " Found existing installation: transformers 4.38.2\n", " Uninstalling transformers-4.38.2:\n", " Successfully uninstalled transformers-4.38.2\n", "Successfully installed GitPython-3.1.42 accelerate-0.27.1 bitsandbytes-0.41.3 datasets-2.18.0 dill-0.3.8 docker-pycreds-0.4.0 docstring-parser-0.16 gitdb-4.0.11 multiprocess-0.70.16 peft-0.8.2 sentry-sdk-1.43.0 setproctitle-1.3.3 shtab-1.7.1 smmap-5.0.1 transformers-4.40.0.dev0 trl-0.7.10 tyro-0.7.3 wandb-0.16.3 xxhash-3.4.1\n" ] } ] }, { "cell_type": "code", "source": [ "%pwd" ], "metadata": { "execution": { "iopub.status.busy": "2024-03-19T20:03:57.777954Z", "iopub.execute_input": "2024-03-19T20:03:57.778381Z", "iopub.status.idle": "2024-03-19T20:03:57.788089Z", "shell.execute_reply.started": "2024-03-19T20:03:57.778345Z", "shell.execute_reply": "2024-03-19T20:03:57.787200Z" }, "trusted": true, "colab": { "base_uri": "https://localhost:8080/", "height": 35 }, "id": "MDdUs8ZB0sZ3", "outputId": "18792733-9e19-4748-e088-f7ca6edf9941" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "'/content/starcoder2'" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" } }, "metadata": {}, "execution_count": 6 } ] }, { "cell_type": "code", "source": [ "import wandb\n", "wandb.login()" ], "metadata": { "execution": { "iopub.status.busy": "2024-03-19T20:03:57.789710Z", "iopub.execute_input": "2024-03-19T20:03:57.790002Z", "iopub.status.idle": "2024-03-19T20:04:11.138702Z", "shell.execute_reply.started": "2024-03-19T20:03:57.789976Z", "shell.execute_reply": "2024-03-19T20:04:11.137773Z" }, "trusted": true, "colab": { "base_uri": "https://localhost:8080/", "height": 121 }, "id": "9QDruTSo0sZ3", "outputId": "f6c13c74-754b-4d0e-cd18-049b771d2e7e" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "" ], "application/javascript": [ "\n", " window._wandbApiKey = new Promise((resolve, reject) => {\n", " function loadScript(url) {\n", " return new Promise(function(resolve, reject) {\n", " let newScript = document.createElement(\"script\");\n", " newScript.onerror = reject;\n", " newScript.onload = resolve;\n", " document.body.appendChild(newScript);\n", " newScript.src = url;\n", " });\n", " }\n", " loadScript(\"https://cdn.jsdelivr.net/npm/postmate/build/postmate.min.js\").then(() => {\n", " const iframe = document.createElement('iframe')\n", " iframe.style.cssText = \"width:0;height:0;border:none\"\n", " document.body.appendChild(iframe)\n", " const handshake = new Postmate({\n", " container: iframe,\n", " url: 'https://wandb.ai/authorize'\n", " });\n", " const timeout = setTimeout(() => reject(\"Couldn't auto authenticate\"), 5000)\n", " handshake.then(function(child) {\n", " child.on('authorize', data => {\n", " clearTimeout(timeout)\n", " resolve(data)\n", " });\n", " });\n", " })\n", " });\n", " " ] }, "metadata": {} }, { "output_type": "stream", "name": "stderr", "text": [ "\u001b[34m\u001b[1mwandb\u001b[0m: Logging into wandb.ai. (Learn how to deploy a W&B server locally: https://wandb.me/wandb-server)\n", "\u001b[34m\u001b[1mwandb\u001b[0m: You can find your API key in your browser here: https://wandb.ai/authorize\n", "wandb: Paste an API key from your profile and hit enter, or press ctrl+c to quit:" ] }, { "name": "stdout", "output_type": "stream", "text": [ " ··········\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "True" ] }, "metadata": {}, "execution_count": 7 } ] }, { "cell_type": "code", "source": [ "from huggingface_hub import notebook_login\n", "\n", "notebook_login()" ], "metadata": { "execution": { "iopub.status.busy": "2024-03-19T20:04:11.139793Z", "iopub.execute_input": "2024-03-19T20:04:11.140165Z", "iopub.status.idle": "2024-03-19T20:04:11.292102Z", "shell.execute_reply.started": "2024-03-19T20:04:11.140141Z", "shell.execute_reply": "2024-03-19T20:04:11.291085Z" }, "trusted": true, "colab": { "base_uri": "https://localhost:8080/", "height": 145, "referenced_widgets": [ "1234072a81334f8db0a10d1b44d034f5", "0b7664f082d34d9b9b86979e0a7f55e7", "5b777f1e81ff439b8dca5e5d9eedf67b", "3c3e316bad6542ee8da7b7d478bc0de0", "48c07121dcd247bb96d38eb1bdd2a073", "663c38b3e97c4855a959bbc4582c2412", "34ba7411d5de41c9ac7ef9ade5a5ad9b", "aec899db50df4647ae5ac36c07ee294f", "d5f8193d213d4860aaa0c842ba7c9c07", "eed45bc885fd4adcbce829b0c9afbf48", "d2fdd03aa4e148bcac64eab9229af61c", "917ad72239a24a2ca19578077bd3f190", "c08f5bb3f3b0400eac10e333a78f30b8", "8594f76b97fa4814a5ae0235f3ad0961", "bea5cf62b00b446bb2ef49329771a398", "a1667ab01c674d93b8456e84ea587d03", "1504ebc3efdf41b5854a6596a175aedb", "7b5c33a1c5b44424b673c2d7611013e9", "468b9dc57b164213b7e58acc369f5c0d", "7923884bad934c0ca2c1a47529d65325", "6bba1b4558b0432aa44c558e5d4ebdf8", "4ac3b065ad9546398e2691ceb371c233", "accba8f890814d5f92464b3471966bbf", "bb0db85e948443019c9d645280175b47", "505b4a8563564747a4f4ac0934ce58ca", "fd9c755b79314b858fe405bf087f80f6", "8a7d1ba404dd49a1bb517d12f7a993f6", "18d9e77db3da4e23902226007712d51d", "a30e755f34e142f8baab95721c9b9870", "15d307d0cd1540f6af402f319a668e05", "87ce8a9512264f15b3804982249aed56", "da3475cbed5240c3a5b860377caa0697" ] }, "id": "IdMgve-D0sZ3", "outputId": "42bc84b3-2421-4663-bb03-6d9b220d1391" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "VBox(children=(HTML(value='
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already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->datasets->trl==0.7.12.dev0) (1.16.0)\n", "Building wheels for collected packages: trl\n", " Building wheel for trl (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", " Created wheel for trl: filename=trl-0.7.12.dev0-py3-none-any.whl size=173433 sha256=53a43dc49d7d8c02ff9a31724023c0fb3c1b64348ccce2eea04682f7dde954c6\n", " Stored in directory: /root/.cache/pip/wheels/ad/f5/b1/f5ac48230936583c88cfde8596bc92cad4b0a4b24d0f819c06\n", "Successfully built trl\n", "Installing collected packages: trl\n", " Attempting uninstall: trl\n", " Found existing installation: trl 0.7.10\n", " Uninstalling trl-0.7.10:\n", " Successfully uninstalled trl-0.7.10\n", "Successfully installed trl-0.7.12.dev0\n" ] } ] }, { "cell_type": "code", "source": [ "# Code adapted from https://github.com/huggingface/trl/blob/main/examples/research_projects/stack_llama/scripts/supervised_finetuning.py\n", "# and https://huggingface.co/blog/gemma-peft\n", "import argparse\n", "import multiprocessing\n", "import os\n", "\n", "import torch\n", "import transformers\n", "from accelerate import PartialState\n", "from datasets import load_dataset\n", "from peft import LoraConfig\n", "from transformers import (\n", " AutoModelForCausalLM,\n", " BitsAndBytesConfig,\n", " logging,\n", " set_seed,\n", ")\n", "from trl import SFTTrainer\n", "\n" ], "metadata": { "execution": { "iopub.status.busy": "2024-03-19T20:04:39.980277Z", "iopub.execute_input": "2024-03-19T20:04:39.980608Z", "iopub.status.idle": "2024-03-19T20:04:56.922413Z", "shell.execute_reply.started": "2024-03-19T20:04:39.980583Z", "shell.execute_reply": "2024-03-19T20:04:56.921624Z" }, "trusted": true, "id": "qQuVp9kt0sZ3" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "\n", "\n", "parser = argparse.ArgumentParser()\n", "parser.add_argument(\"--model_id\", type=str, default=\"bigcode/starcoder2-3b\")\n", "parser.add_argument(\"--dataset_name\", type=str, default=\"bigcode/the-stack-smol\")\n", "parser.add_argument(\"--subset\", type=str, default=\"data/sql\")\n", "parser.add_argument(\"--split\", type=str, default=\"train\")\n", "parser.add_argument(\"--dataset_text_field\", type=str, default=\"content\")\n", "\n", "parser.add_argument(\"--max_seq_length\", type=int, default=512)\n", "parser.add_argument(\"--max_steps\", type=int, default=1000)\n", "parser.add_argument(\"--micro_batch_size\", type=int, default=1)\n", "parser.add_argument(\"--gradient_accumulation_steps\", type=int, default=4)\n", "parser.add_argument(\"--weight_decay\", type=float, default=0.01)\n", "parser.add_argument(\"--fp16\", type=bool, default=True)\n", "\n", "parser.add_argument(\"--attention_dropout\", type=float, default=0.1)\n", "parser.add_argument(\"--learning_rate\", type=float, default=2e-4)\n", "parser.add_argument(\"--lr_scheduler_type\", type=str, default=\"cosine\")\n", "parser.add_argument(\"--warmup_steps\", type=int, default=100)\n", "parser.add_argument(\"--seed\", type=int, default=0)\n", "parser.add_argument(\"--output_dir\", type=str, default=\"finetune_starcoder2\")\n", "parser.add_argument(\"--num_proc\", type=int, default=2)#was none since i have 2 gpus why not\n", "parser.add_argument(\"--push_to_hub\", type=bool, default=True)\n", "\n", "args = parser.parse_args(args=[])\n" ], "metadata": { "execution": { "iopub.status.busy": "2024-03-19T20:04:56.923522Z", "iopub.execute_input": "2024-03-19T20:04:56.924095Z", "iopub.status.idle": "2024-03-19T20:04:56.935605Z", "shell.execute_reply.started": "2024-03-19T20:04:56.924067Z", "shell.execute_reply": "2024-03-19T20:04:56.934593Z" }, "trusted": true, "id": "GRT0JgpF0sZ4" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "args" ], "metadata": { "execution": { "iopub.status.busy": "2024-03-19T20:04:56.936862Z", "iopub.execute_input": "2024-03-19T20:04:56.937191Z", "iopub.status.idle": "2024-03-19T20:04:56.966429Z", "shell.execute_reply.started": "2024-03-19T20:04:56.937157Z", "shell.execute_reply": "2024-03-19T20:04:56.965564Z" }, "trusted": true, "colab": { "base_uri": "https://localhost:8080/" }, "id": "gaSUzOv40sZ4", "outputId": "1f56d30a-c60c-476e-cc4c-34f74286f63f" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "Namespace(model_id='bigcode/starcoder2-3b', dataset_name='bigcode/the-stack-smol', subset='data/sql', split='train', dataset_text_field='content', max_seq_length=512, max_steps=1000, micro_batch_size=1, gradient_accumulation_steps=4, weight_decay=0.01, fp16=True, attention_dropout=0.1, learning_rate=0.0002, lr_scheduler_type='cosine', warmup_steps=100, seed=0, output_dir='finetune_starcoder2', num_proc=2, push_to_hub=True)" ] }, "metadata": {}, "execution_count": 12 } ] }, { "cell_type": "code", "source": [ "\n", "def print_trainable_parameters(model):\n", " \"\"\"\n", " Prints the number of trainable parameters in the model.\n", " \"\"\"\n", " trainable_params = 0\n", " all_param = 0\n", " for _, param in model.named_parameters():\n", " all_param += param.numel()\n", " if param.requires_grad:\n", " trainable_params += param.numel()\n", " print(\n", " f\"trainable params: {trainable_params} || all params: {all_param} || trainable%: {100 * trainable_params / all_param}\"\n", " )\n", "\n", "\n" ], "metadata": { "execution": { "iopub.status.busy": "2024-03-19T20:04:56.967468Z", "iopub.execute_input": "2024-03-19T20:04:56.967754Z", "iopub.status.idle": "2024-03-19T20:04:56.975477Z", "shell.execute_reply.started": "2024-03-19T20:04:56.967732Z", "shell.execute_reply": "2024-03-19T20:04:56.974545Z" }, "trusted": true, "id": "VdpvW4A60sZ4" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "def main(args):\n", " # config\n", " bnb_config = BitsAndBytesConfig(\n", " load_in_4bit=True,\n", " bnb_4bit_quant_type=\"nf4\",\n", " bnb_4bit_compute_dtype=torch.bfloat16,\n", " )\n", " lora_config = LoraConfig(\n", " r=8,\n", " target_modules=[\n", " \"q_proj\",\n", " \"o_proj\",\n", " \"k_proj\",\n", " \"v_proj\",\n", " \"gate_proj\",\n", " \"up_proj\",\n", " \"down_proj\",\n", " ],\n", " task_type=\"CAUSAL_LM\",\n", " )\n", "\n", " # load model and dataset\n", " token = os.environ.get(\"HF_TOKEN\", None)\n", " model = AutoModelForCausalLM.from_pretrained(\n", " args.model_id,\n", " quantization_config=bnb_config,\n", " device_map={\"\": PartialState().process_index},\n", " attention_dropout=args.attention_dropout,\n", " )\n", " print_trainable_parameters(model)\n", "\n", " data = load_dataset(\n", " args.dataset_name,\n", " data_dir=args.subset,\n", " split=args.split,\n", " token=token,\n", " num_proc=args.num_proc if args.num_proc else multiprocessing.cpu_count(),\n", " )\n", "\n", " # setup the trainer\n", " trainer = SFTTrainer(\n", " model=model,\n", " train_dataset=data,\n", " max_seq_length=args.max_seq_length,\n", " args=transformers.TrainingArguments(\n", " per_device_train_batch_size=args.micro_batch_size,\n", " gradient_accumulation_steps=args.gradient_accumulation_steps,\n", " warmup_steps=args.warmup_steps,\n", " max_steps=args.max_steps,\n", " learning_rate=args.learning_rate,\n", " lr_scheduler_type=args.lr_scheduler_type,\n", " weight_decay=args.weight_decay,\n", " fp16=args.fp16,\n", " logging_strategy=\"steps\",\n", " logging_steps=10,\n", " output_dir=args.output_dir,\n", " optim=\"paged_adamw_8bit\",\n", " seed=args.seed,\n", " run_name=f\"train-{args.model_id.split('/')[-1]}\",\n", " report_to=\"wandb\",\n", " ),\n", " peft_config=lora_config,\n", " dataset_text_field=args.dataset_text_field,\n", " )\n", "\n", " # launch\n", " print(\"Training...\")\n", " trainer.train()\n", "\n", " print(\"Saving the last checkpoint of the model\")\n", " model.save_pretrained(os.path.join(args.output_dir, \"final_checkpoint/\"))\n", " if args.push_to_hub:\n", " trainer.push_to_hub(\"Upload model\")\n", " print(\"Training Done! 💥\")" ], "metadata": { "execution": { "iopub.status.busy": "2024-03-19T20:04:56.976790Z", "iopub.execute_input": "2024-03-19T20:04:56.977037Z", "iopub.status.idle": "2024-03-19T20:04:56.988637Z", "shell.execute_reply.started": "2024-03-19T20:04:56.977015Z", "shell.execute_reply": "2024-03-19T20:04:56.987799Z" }, "trusted": true, "id": "uJ6zaIcX0sZ4" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "set_seed(args.seed)\n", "os.makedirs(args.output_dir, exist_ok=True)\n", "\n", "logging.set_verbosity_error()\n", "\n", "main(args)" ], "metadata": { "execution": { "iopub.status.busy": "2024-03-19T20:05:53.664781Z", "iopub.execute_input": "2024-03-19T20:05:53.665168Z" }, "trusted": true, "colab": { "base_uri": "https://localhost:8080/", "height": 1000, "referenced_widgets": [ "ac5e93b72ad84752b974c04b8f4b51f9", "595a2f42de714f18a84afa6285659917", "02a3c25f3e0a4a6d96e45b7b3498bee3", 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To upgrade, please run:\n", " $ pip install wandb --upgrade" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "Tracking run with wandb version 0.16.3" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "Run data is saved locally in /content/starcoder2/wandb/run-20240322_122024-ww6p0lwc" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "Syncing run train-starcoder2-3b to Weights & Biases (docs)
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