diff --git "a/smollm2_1_7b_instruct_lrsc_linear_hindi_subset_drishti.ipynb" "b/smollm2_1_7b_instruct_lrsc_linear_hindi_subset_drishti.ipynb"
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+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "890a4b2a-0657-4c5c-8e01-a43dc1ef9c83",
+ "metadata": {
+ "id": "890a4b2a-0657-4c5c-8e01-a43dc1ef9c83",
+ "outputId": "28e04e99-9bef-4fdc-c68c-662555fdb576"
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Collecting huggingface_hub\n",
+ " Downloading huggingface_hub-0.27.1-py3-none-any.whl.metadata (13 kB)\n",
+ "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (3.9.0)\n",
+ "Collecting fsspec>=2023.5.0 (from huggingface_hub)\n",
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+ "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (23.2)\n",
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+ "Collecting tqdm>=4.42.1 (from huggingface_hub)\n",
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+ "\u001b[?25hInstalling collected packages: tqdm, fsspec, huggingface_hub\n",
+ " Attempting uninstall: fsspec\n",
+ " Found existing installation: fsspec 2023.4.0\n",
+ " Uninstalling fsspec-2023.4.0:\n",
+ " Successfully uninstalled fsspec-2023.4.0\n",
+ "Successfully installed fsspec-2024.12.0 huggingface_hub-0.27.1 tqdm-4.67.1\n",
+ "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\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;49m23.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.3.1\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;49mpython -m pip install --upgrade pip\u001b[0m\n"
+ ]
+ }
+ ],
+ "source": [
+ "!pip install huggingface_hub"
+ ]
+ },
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+ "execution_count": null,
+ "id": "y1jMmutu5wf2",
+ "metadata": {
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+ "outputId": "b456c8d8-79a0-410e-eae5-9ded7ff7dd58"
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+ "\u001b[?25hDownloading yarl-1.18.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (319 kB)\n",
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+ "\u001b[?25hDownloading mdurl-0.1.2-py3-none-any.whl (10.0 kB)\n",
+ "Installing collected packages: sentencepiece, pytz, xxhash, wheel, tzdata, typing-extensions, triton, sympy, shtab, safetensors, requests, regex, pyarrow, protobuf, propcache, 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, mdurl, hf_transfer, fsspec, frozenlist, docstring-parser, dill, async-timeout, aiohappyeyeballs, typeguard, pandas, nvidia-cusparse-cu12, nvidia-cudnn-cu12, multiprocess, multidict, markdown-it-py, aiosignal, yarl, tokenizers, rich, nvidia-cusolver-cu12, tyro, transformers, torch, aiohttp, xformers, cut_cross_entropy, bitsandbytes, accelerate, peft, datasets, trl, unsloth_zoo, unsloth\n",
+ " Attempting uninstall: wheel\n",
+ " Found existing installation: wheel 0.41.3\n",
+ " Uninstalling wheel-0.41.3:\n",
+ " Successfully uninstalled wheel-0.41.3\n",
+ " Attempting uninstall: typing-extensions\n",
+ " Found existing installation: typing_extensions 4.4.0\n",
+ " Uninstalling typing_extensions-4.4.0:\n",
+ " Successfully uninstalled typing_extensions-4.4.0\n",
+ " Attempting uninstall: triton\n",
+ " Found existing installation: triton 2.1.0\n",
+ " Uninstalling triton-2.1.0:\n",
+ " Successfully uninstalled triton-2.1.0\n",
+ " Attempting uninstall: sympy\n",
+ " Found existing installation: sympy 1.12\n",
+ " Uninstalling sympy-1.12:\n",
+ " Successfully uninstalled sympy-1.12\n",
+ " Attempting uninstall: requests\n",
+ " Found existing installation: requests 2.31.0\n",
+ " Uninstalling requests-2.31.0:\n",
+ " Successfully uninstalled requests-2.31.0\n",
+ " Attempting uninstall: fsspec\n",
+ " Found existing installation: fsspec 2024.12.0\n",
+ " Uninstalling fsspec-2024.12.0:\n",
+ " Successfully uninstalled fsspec-2024.12.0\n",
+ " Attempting uninstall: torch\n",
+ " Found existing installation: torch 2.1.0+cu118\n",
+ " Uninstalling torch-2.1.0+cu118:\n",
+ " Successfully uninstalled torch-2.1.0+cu118\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",
+ "torchaudio 2.1.0+cu118 requires torch==2.1.0, but you have torch 2.5.1 which is incompatible.\n",
+ "torchvision 0.16.0+cu118 requires torch==2.1.0, but you have torch 2.5.1 which is incompatible.\u001b[0m\u001b[31m\n",
+ "\u001b[0mSuccessfully installed accelerate-1.3.0 aiohappyeyeballs-2.4.4 aiohttp-3.11.11 aiosignal-1.3.2 async-timeout-5.0.1 bitsandbytes-0.45.0 cut_cross_entropy-25.1.1 datasets-3.2.0 dill-0.3.8 docstring-parser-0.16 frozenlist-1.5.0 fsspec-2024.9.0 hf_transfer-0.1.9 markdown-it-py-3.0.0 mdurl-0.1.2 multidict-6.1.0 multiprocess-0.70.16 nvidia-cublas-cu12-12.4.5.8 nvidia-cuda-cupti-cu12-12.4.127 nvidia-cuda-nvrtc-cu12-12.4.127 nvidia-cuda-runtime-cu12-12.4.127 nvidia-cudnn-cu12-9.1.0.70 nvidia-cufft-cu12-11.2.1.3 nvidia-curand-cu12-10.3.5.147 nvidia-cusolver-cu12-11.6.1.9 nvidia-cusparse-cu12-12.3.1.170 nvidia-nccl-cu12-2.21.5 nvidia-nvjitlink-cu12-12.4.127 nvidia-nvtx-cu12-12.4.127 pandas-2.2.3 peft-0.14.0 propcache-0.2.1 protobuf-3.20.3 pyarrow-19.0.0 pytz-2024.2 regex-2024.11.6 requests-2.32.3 rich-13.9.4 safetensors-0.5.2 sentencepiece-0.2.0 shtab-1.7.1 sympy-1.13.1 tokenizers-0.21.0 torch-2.5.1 transformers-4.48.0 triton-3.1.0 trl-0.13.0 typeguard-4.4.1 typing-extensions-4.12.2 tyro-0.9.10 tzdata-2024.2 unsloth-2025.1.5 unsloth_zoo-2025.1.3 wheel-0.45.1 xformers-0.0.29.post1 xxhash-3.5.0 yarl-1.18.3\n",
+ "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\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;49m23.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.3.1\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;49mpython -m pip install --upgrade pip\u001b[0m\n",
+ "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (23.2)\n",
+ "Collecting ninja\n",
+ " Downloading ninja-1.11.1.3-py3-none-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.metadata (5.3 kB)\n",
+ "Collecting einops\n",
+ " Downloading einops-0.8.0-py3-none-any.whl.metadata (12 kB)\n",
+ "Collecting flash-attn>=2.6.3\n",
+ " Downloading flash_attn-2.7.3.tar.gz (3.2 MB)\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.2/3.2 MB\u001b[0m \u001b[31m1.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
+ "\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25ldone\n",
+ "\u001b[?25hUsing cached ninja-1.11.1.3-py3-none-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (422 kB)\n",
+ "Downloading einops-0.8.0-py3-none-any.whl (43 kB)\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m43.2/43.2 kB\u001b[0m \u001b[31m2.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[?25hBuilding wheels for collected packages: flash-attn\n",
+ " Building wheel for flash-attn (setup.py) ... \u001b[?25ldone\n",
+ "\u001b[?25h Created wheel for flash-attn: filename=flash_attn-2.7.3-cp310-cp310-linux_x86_64.whl size=191342964 sha256=cd0ead6ad92bff21f90cf0aecdf859bc7145bf4e7dc8ed1fdc3cc38299651ce4\n",
+ " Stored in directory: /root/.cache/pip/wheels/85/d7/10/a74c9fe5ffe6ff306b27a220b2bf2f37d907b68fdcd138cdda\n",
+ "Successfully built flash-attn\n",
+ "Installing collected packages: ninja, flash-attn, einops\n",
+ "Successfully installed einops-0.8.0 flash-attn-2.7.3 ninja-1.11.1.3\n",
+ "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\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;49m23.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.3.1\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;49mpython -m pip install --upgrade pip\u001b[0m\n"
+ ]
+ }
+ ],
+ "source": [
+ "! pip install unsloth --upgrade --no-cache-dir\n",
+ "import torch\n",
+ "if torch.cuda.get_device_capability()[0] >= 8:\n",
+ " !pip install --no-deps packaging ninja einops \"flash-attn>=2.6.3\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "6c7ca839-be08-4b49-ba49-d242cfdaf618",
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 412,
+ "referenced_widgets": [
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+ ]
+ },
+ "id": "6c7ca839-be08-4b49-ba49-d242cfdaf618",
+ "outputId": "0f0e3793-0049-4ff1-abf4-b877f92284e5"
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n",
+ "Unsloth: Your Flash Attention 2 installation seems to be broken?\n",
+ "A possible explanation is you have a new CUDA version which isn't\n",
+ "yet compatible with FA2? Please file a ticket to Unsloth or FA2.\n",
+ "We shall now use Xformers instead, which does not have any performance hits!\n",
+ "We found this negligible impact by benchmarking on 1x A100.\n",
+ "🦥 Unsloth Zoo will now patch everything to make training faster!\n",
+ "==((====))== Unsloth 2025.1.5: Fast Llama patching. Transformers: 4.48.0.\n",
+ " \\\\ /| GPU: NVIDIA A100 80GB PCIe. Max memory: 79.138 GB. Platform: Linux.\n",
+ "O^O/ \\_/ \\ Torch: 2.5.1+cu124. CUDA: 8.0. CUDA Toolkit: 12.4. Triton: 3.1.0\n",
+ "\\ / Bfloat16 = TRUE. FA [Xformers = 0.0.29.post1. FA2 = False]\n",
+ " \"-____-\" Free Apache license: http://github.com/unslothai/unsloth\n",
+ "Unsloth: Fast downloading is enabled - ignore downloading bars which are red colored!\n"
+ ]
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "98fd34d2d3e0489782c49865876055de",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "model.safetensors: 0%| | 0.00/3.42G [00:00, ?B/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "4f29ac7623da4b58bd5446c0cad37704",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "generation_config.json: 0%| | 0.00/158 [00:00, ?B/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "00b69390dac44d25be2e284939584625",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "tokenizer_config.json: 0%| | 0.00/4.14k [00:00, ?B/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "b19fcd0e689646cc967dc97f3de05391",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "vocab.json: 0%| | 0.00/801k [00:00, ?B/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "c51ec2553fc74293a440f047a5fc0e90",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "merges.txt: 0%| | 0.00/466k [00:00, ?B/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "2e418de8703a4d37adc9077e60144618",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "added_tokens.json: 0%| | 0.00/29.0 [00:00, ?B/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "9e89feb5ff0a468a99ef24c9ce41de5d",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "special_tokens_map.json: 0%| | 0.00/423 [00:00, ?B/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "3079e288b7134ecf945a260ac221b934",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "tokenizer.json: 0%| | 0.00/3.52M [00:00, ?B/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from unsloth import FastLanguageModel\n",
+ "import torch\n",
+ "max_seq_length = 2048\n",
+ "dtype = None\n",
+ "load_in_4bit = False\n",
+ "model, tokenizer = FastLanguageModel.from_pretrained(model_name = \"unsloth/SmolLM2-1.7B-Instruct\", max_seq_length = max_seq_length, dtype = dtype, load_in_4bit = load_in_4bit,)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "6296c071-fa11-407d-a6a8-95a160cfb2f5",
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "6296c071-fa11-407d-a6a8-95a160cfb2f5",
+ "outputId": "7abd16b8-692c-46c1-bb54-fcea392621ad"
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "Unsloth 2025.1.5 patched 24 layers with 24 QKV layers, 24 O layers and 24 MLP layers.\n"
+ ]
+ }
+ ],
+ "source": [
+ "model = FastLanguageModel.get_peft_model(model, r = 16, target_modules = [\"q_proj\", \"k_proj\", \"v_proj\", \"o_proj\", \"gate_proj\", \"up_proj\", \"down_proj\",],\n",
+ " lora_alpha = 16, lora_dropout = 0, bias = \"none\", use_gradient_checkpointing = \"unsloth\", random_state = 1024, use_rslora = False, loftq_config = None,)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "70a60388-9e5b-4915-a624-3c58dd71c275",
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 81,
+ "referenced_widgets": [
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+ ]
+ },
+ "id": "70a60388-9e5b-4915-a624-3c58dd71c275",
+ "outputId": "cb150b2a-2f44-4c87-9d86-ad5317c93d9a"
+ },
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "2e5168b14ebf44c28fb4a2cf41c269a5",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "hindi-gemma-mini-subset.csv: 0%| | 0.00/54.9M [00:00, ?B/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "b6ca51a2e59a44f4b642df5eabbdc664",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Generating train split: 0 examples [00:00, ? examples/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from datasets import load_dataset\n",
+ "import os\n",
+ "dataset = load_dataset(\"1-800-LLMs/Data-Collection\", data_files=\"hindi-gemma-mini-subset.csv\", split=\"train\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "6MNXXvi86Bo5",
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 423
+ },
+ "id": "6MNXXvi86Bo5",
+ "outputId": "d82fcaa1-11df-4431-8a65-ed1e2286b7fe"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
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+ " \n",
+ " \n",
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+ " Yes. But typing should be in capital letters ... | \n",
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\n",
+ " \n",
+ " 1 | \n",
+ " क्या भाषा आधारित अल्पसंख्यकों के लिए विशेष अधि... | \n",
+ " भाषाई अल्पसंख्यकों के विशेष अधिकारी की भूमिका ... | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " क्या एक अध्यादेश संघ क्षेत्र की विधान सभा द्वा... | \n",
+ " नहीं, एक अध्यादेश संघ क्षेत्र की विधान सभा द्व... | \n",
+ "
\n",
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\n",
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\n",
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\n",
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+ " 32716 | \n",
+ " What is the Constitutional mandate of the Unio... | \n",
+ " Union Public Service Commission is a Constitut... | \n",
+ "
\n",
+ " \n",
+ " 32717 | \n",
+ " मैंने क्रेडिट/डेबिट कार्ड के जरिए कई बार भुगता... | \n",
+ " हाँ, आवेदन नंबर के खिलाफ किए गए अतिरिक्त भुगता... | \n",
+ "
\n",
+ " \n",
+ " 32718 | \n",
+ " मैं अपनी ऑनलाइन भर्ती आवेदन (ORA) को पूरा करने... | \n",
+ " कृपया इस प्रकार आगे बढ़ें:- चरण 1 - सुनिश्चित ... | \n",
+ "
\n",
+ " \n",
+ " 32719 | \n",
+ " क्या एक अधिकारी जिसकी ईमानदारी प्रमाणपत्र राज्... | \n",
+ " नहीं। | \n",
+ "
\n",
+ " \n",
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+ " अगर फोटो इच्छित प्रारूप में नहीं है, तो मैं इस... | \n",
+ " यदि छवि किसी अन्य प्रारूप में है जैसे .tiff, .... | \n",
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+ "32718 मैं अपनी ऑनलाइन भर्ती आवेदन (ORA) को पूरा करने... \n",
+ "32719 क्या एक अधिकारी जिसकी ईमानदारी प्रमाणपत्र राज्... \n",
+ "32720 अगर फोटो इच्छित प्रारूप में नहीं है, तो मैं इस... \n",
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+ "1 भाषाई अल्पसंख्यकों के विशेष अधिकारी की भूमिका ... \n",
+ "2 नहीं, एक अध्यादेश संघ क्षेत्र की विधान सभा द्व... \n",
+ "3 Yes, a law made under clause (1) can establish... \n",
+ "4 The speed limit for electric scooters in India... \n",
+ "... ... \n",
+ "32716 Union Public Service Commission is a Constitut... \n",
+ "32717 हाँ, आवेदन नंबर के खिलाफ किए गए अतिरिक्त भुगता... \n",
+ "32718 कृपया इस प्रकार आगे बढ़ें:- चरण 1 - सुनिश्चित ... \n",
+ "32719 नहीं। \n",
+ "32720 यदि छवि किसी अन्य प्रारूप में है जैसे .tiff, .... \n",
+ "\n",
+ "[32721 rows x 2 columns]"
+ ]
+ },
+ "execution_count": 8,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df = dataset.to_pandas()\n",
+ "df"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "c66206ed-8628-45bf-9c8d-f7d73548e9f0",
+ "metadata": {
+ "id": "c66206ed-8628-45bf-9c8d-f7d73548e9f0"
+ },
+ "outputs": [],
+ "source": [
+ "alpaca_prompt = \"\"\"### INPUT: {} ### RESPONSE: {}\"\"\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "fc3addd1-d898-4334-8cce-df995b964f99",
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 49,
+ "referenced_widgets": [
+ "5e7a468fd6dc4bc09c691d7666c30421",
+ "1b6489b45379462ca305c561115209e5",
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+ "15290529eed746f0bd227ed622191ba0"
+ ]
+ },
+ "id": "fc3addd1-d898-4334-8cce-df995b964f99",
+ "outputId": "f705140c-35f3-4af0-eb22-a3b0782e01b9"
+ },
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "15290529eed746f0bd227ed622191ba0",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Map: 0%| | 0/32721 [00:00, ? examples/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "EOS_TOKEN = tokenizer.eos_token\n",
+ "def formatting_prompts_func(examples):\n",
+ " inputs = examples[\"Input\"]\n",
+ " outputs = examples[\"Output\"]\n",
+ " texts = []\n",
+ " for input_text, output_text in zip(inputs, outputs):\n",
+ " text = alpaca_prompt.format(input_text, output_text) + EOS_TOKEN\n",
+ " texts.append(text)\n",
+ " return {\"text\": texts}\n",
+ "dataset = dataset.map(formatting_prompts_func, batched=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "98c993c3-9845-4275-8438-8ceef5d0e6ee",
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 49,
+ "referenced_widgets": [
+ "4b770d73809c41779b6c5f7be290a6b1",
+ "305c512c9df3453c961c84fffb534648",
+ "7277d74f7222464abd7be1b6716cbeb6",
+ "a4f791ee89b84766a5f5c7c4b1ccf777",
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+ "422451ba560544f1af96e883d37a31c2",
+ "165e7b40e66d45798753f4c108b63d61"
+ ]
+ },
+ "id": "98c993c3-9845-4275-8438-8ceef5d0e6ee",
+ "outputId": "1d418439-d9a7-41d5-f6e9-abc867f91b97"
+ },
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "165e7b40e66d45798753f4c108b63d61",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Map: 0%| | 0/32721 [00:00, ? examples/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "def count_tokens(example):\n",
+ " return {\"input_token_count\": len(tokenizer.tokenize(str(example.get(\"Input\", \"\"))))}\n",
+ "dataset = dataset.map(count_tokens)\n",
+ "dataset = dataset.sort(\"input_token_count\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "ceFDXKVU7U3x",
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 49,
+ "referenced_widgets": [
+ "94b56f00232a41bcb4af46125f98539a",
+ "b2ec97cc62614a708cdf18ab0750a87d",
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+ "4b176c4c041c4085950029e1e27ca94a",
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+ ]
+ },
+ "id": "ceFDXKVU7U3x",
+ "outputId": "19c1fa9a-003b-402b-d797-c120b7ece6ff"
+ },
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "9995de66ebb5486ea7e800923bd1a0f3",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Flattening the indices: 0%| | 0/32721 [00:00, ? examples/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from datasets import concatenate_datasets\n",
+ "last_200 = dataset.select(range(len(dataset) - 200, len(dataset)))\n",
+ "remaining = dataset.select(range(len(dataset) - 200))\n",
+ "dataset = concatenate_datasets([last_200, remaining])\n",
+ "dataset = dataset.flatten_indices()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "3f98893b-dace-422f-93da-04a7f8eb71f2",
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 49,
+ "referenced_widgets": [
+ "90093e88a13b41048cb6f85f94ff243f",
+ "6088fa1083a841c2a00a3a426cae1bef",
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+ "12fecd83cf8048fe85c7a44de970ccb0",
+ "85e396bc539e47ebb88b59a60128b38a"
+ ]
+ },
+ "id": "3f98893b-dace-422f-93da-04a7f8eb71f2",
+ "outputId": "a25c139a-b591-4c2b-fb03-4c893844a24b"
+ },
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "85e396bc539e47ebb88b59a60128b38a",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Map (num_proc=2): 0%| | 0/32721 [00:00, ? examples/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from trl import SFTTrainer\n",
+ "from transformers import TrainingArguments\n",
+ "from unsloth import is_bfloat16_supported\n",
+ "trainer = SFTTrainer(\n",
+ " model = model,\n",
+ " tokenizer = tokenizer,\n",
+ " train_dataset = dataset,\n",
+ " dataset_text_field = \"text\",\n",
+ " max_seq_length = max_seq_length,\n",
+ " dataset_num_proc = 2,\n",
+ " packing = False,\n",
+ " args = TrainingArguments(\n",
+ " per_device_train_batch_size = 8,\n",
+ " gradient_accumulation_steps = 12,\n",
+ " num_train_epochs = 1,\n",
+ " learning_rate = 2e-5,\n",
+ " fp16 = not is_bfloat16_supported(),\n",
+ " bf16 = is_bfloat16_supported(),\n",
+ " logging_steps = 100,\n",
+ " optim = \"adamw_8bit\",\n",
+ " weight_decay = 0.01,\n",
+ " lr_scheduler_type = \"linear\",\n",
+ " seed = 1024,\n",
+ " output_dir = \"outputs\",\n",
+ " report_to = \"none\",\n",
+ " ),\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "9e6f6b98-01d5-4088-a284-f37fb660e761",
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 162
+ },
+ "id": "9e6f6b98-01d5-4088-a284-f37fb660e761",
+ "outputId": "4792ae90-eba6-436d-c13c-6ec81952890f"
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "==((====))== Unsloth - 2x faster free finetuning | Num GPUs = 1\n",
+ " \\\\ /| Num examples = 32,721 | Num Epochs = 1\n",
+ "O^O/ \\_/ \\ Batch size per device = 8 | Gradient Accumulation steps = 12\n",
+ "\\ / Total batch size = 96 | Total steps = 340\n",
+ " \"-____-\" Number of trainable parameters = 18,087,936\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ " \n",
+ " \n",
+ "
\n",
+ " [340/340 1:08:46, Epoch 0/1]\n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " Step | \n",
+ " Training Loss | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 100 | \n",
+ " 1.150100 | \n",
+ "
\n",
+ " \n",
+ " 200 | \n",
+ " 1.058200 | \n",
+ "
\n",
+ " \n",
+ " 300 | \n",
+ " 1.036000 | \n",
+ "
\n",
+ " \n",
+ "
"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "trainer_stats = trainer.train()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "4ZJNyEwMBOel",
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
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+ ]
+ },
+ "id": "4ZJNyEwMBOel",
+ "outputId": "2f3990b2-aa81-4fb5-8ec7-475f3395a517"
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Unsloth: Saving LoRA adapters. Please wait...\n"
+ ]
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "81a1c706e4a44b35a072861d77e87333",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "README.md: 0%| | 0.00/584 [00:00, ?B/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "8af45b5896dd43318c4e703a789c61f7",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "adapter_model.safetensors: 0%| | 0.00/72.4M [00:00, ?B/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Saved lora model to https://huggingface.co/DrishtiSharma/smollm2-1.7b-instruct-hindi-subset\n"
+ ]
+ }
+ ],
+ "source": [
+ "if True: model.push_to_hub_merged(\"DrishtiSharma/smollm2-1.7b-instruct-hindi-subset\", tokenizer, save_method = \"lora\", token = )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "OnyiEx-wyJFR",
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 466,
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+ "output_type": "stream",
+ "text": [
+ "Unsloth: You are pushing to hub, but you passed your HF username = DrishtiSharma.\n",
+ "We shall truncate DrishtiSharma/smollm2-1.7b-instruct-hindi-subset-fp16 to smollm2-1.7b-instruct-hindi-subset-fp16\n"
+ ]
+ },
+ {
+ "name": "stdout",
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+ "text": [
+ "Unsloth: Merging 4bit and LoRA weights to 16bit...\n",
+ "Unsloth: Will use up to 682.79 out of 1007.69 RAM for saving.\n",
+ "Unsloth: Saving model... This might take 5 minutes ...\n"
+ ]
+ },
+ {
+ "name": "stderr",
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+ "text": [
+ "100%|██████████| 24/24 [00:00<00:00, 130.11it/s]\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Unsloth: Saving tokenizer... Done.\n"
+ ]
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+ "README.md: 0%| | 0.00/584 [00:00, ?B/s]"
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+ "metadata": {},
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+ {
+ "name": "stdout",
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+ "text": [
+ "Done.\n",
+ "Saved merged model to https://huggingface.co/DrishtiSharma/smollm2-1.7b-instruct-hindi-subset-fp16\n"
+ ]
+ }
+ ],
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