{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "JeByetuw4Z8p", "outputId": "943173ff-c77f-4d99-fef1-8be42d7741bb" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.11/dist-packages (0.27.1)\n", "Requirement already satisfied: pandas in /usr/local/lib/python3.11/dist-packages (2.2.2)\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (3.16.1)\n", "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (2024.10.0)\n", "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (24.2)\n", "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (6.0.2)\n", "Requirement already satisfied: requests in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (2.32.3)\n", "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (4.67.1)\n", "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (4.12.2)\n", "Requirement already satisfied: numpy>=1.23.2 in /usr/local/lib/python3.11/dist-packages (from pandas) (1.26.4)\n", "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.11/dist-packages (from pandas) (2.8.2)\n", "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas) (2024.2)\n", "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.11/dist-packages (from pandas) (2024.2)\n", "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\n", "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface_hub) (3.4.1)\n", "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface_hub) (3.10)\n", "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface_hub) (2.3.0)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface_hub) (2024.12.14)\n" ] } ], "source": [ "!pip install huggingface_hub pandas" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 17, "referenced_widgets": [ "00e469cfdfcb4a15869a2bb4dc4b143b", "3533f5c716324aaf9dd14322f13d952b", "a4170046417245bba6c13402f16e56e9", "baa8863649ae46dd90a424b954131f81", "dfd7412829c945df890f630f71a81d5b", "7de1017531f24253a7c718798bc52762", "a9dcf075d25e49a3b1e78fa7dec927da", "8e7cb0f4316c485ba2d38b330867fa70", "a10883933fa4450898563771d69c21a8", "7c3246af224c40b08b03cfd63b0ebdff", "4bcb3b10ab3b4747a0619a41b0c3f043", "743e10407eb64de8bbd8da80fd1191c0", "2a22623bd2f047bdbba03a5adebf9f20", "79a5d45e688247b4af48b56f0be41a20", "6d2f15297dee43a9a80bd722e8ade59b", "5c9a77694b904fd2ad01baca262c91c0", "42706d6bb0c745b2b756229716d714d9", "dbe0b3fd792645ecb7e1dda57da64e72", "e32c1c39452b4ace91ac2d992a18b2bc", "e2c867ac1639415a896c328d5473065a" ] }, "id": "-KBQcoiuz-0C", "outputId": "bfb1afec-cdb9-4afd-d58b-a8533024af0a" }, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "VBox(children=(HTML(value='
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This behaviour is the source of the following dependency conflicts.\n", "grpcio-status 1.62.3 requires protobuf>=4.21.6, but you have protobuf 3.20.3 which is incompatible.\n", "gcsfs 2024.10.0 requires fsspec==2024.10.0, but you have fsspec 2024.9.0 which is incompatible.\n", "tensorflow-metadata 1.16.1 requires protobuf<6.0.0dev,>=4.25.2; python_version >= \"3.11\", but you have protobuf 3.20.3 which is incompatible.\u001b[0m\u001b[31m\n", "\u001b[0mSuccessfully installed bitsandbytes-0.45.1 cut_cross_entropy-25.1.1 datasets-3.2.0 dill-0.3.8 fsspec-2024.9.0 hf_transfer-0.1.9 multiprocess-0.70.16 protobuf-3.20.3 shtab-1.7.1 trl-0.13.0 tyro-0.9.13 unsloth-2025.1.6 unsloth_zoo-2025.1.5 xformers-0.0.29.post1 xxhash-3.5.0\n" ] }, { "output_type": "display_data", "data": { "application/vnd.colab-display-data+json": { "pip_warning": { "packages": [ "google" ] }, "id": "f32aa48795324e20879c156c1c48fb18" } }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Requirement already satisfied: packaging in /usr/local/lib/python3.11/dist-packages (24.2)\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", "Requirement already satisfied: einops in /usr/local/lib/python3.11/dist-packages (0.8.0)\n", "Collecting flash-attn>=2.6.3\n", " Downloading flash_attn-2.7.3.tar.gz (3.2 MB)\n", "\u001b[?25l \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/3.2 MB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.2/3.2 MB\u001b[0m \u001b[31m97.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", "Using cached ninja-1.11.1.3-py3-none-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (422 kB)\n", "Building wheels for collected packages: flash-attn\n", " Building wheel for flash-attn (setup.py) ... \u001b[?25l\u001b[?25hdone\n", " Created wheel for flash-attn: filename=flash_attn-2.7.3-cp311-cp311-linux_x86_64.whl size=191363917 sha256=b1243e9b86687348a5ab03a073abacdf8e3d5e9e4b7e5326a183f47348c5dfba\n", " Stored in directory: /root/.cache/pip/wheels/d0/a3/f9/48d2706cb2eac05ec0dc144bf6954fe47bb3c2cd0de280765e\n", "Successfully built flash-attn\n", "Installing collected packages: ninja, flash-attn\n", "Successfully installed flash-attn-2.7.3 ninja-1.11.1.3\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": 16, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 609, "referenced_widgets": [ "fbc875d5c41840659d62ace56a25061c", "809332e70fb245a6a2b17ff0054b15a5", "9e17b2692ec94403b95ee2bfa5177cb9", "a19c9c6f41d246df8ea81b138d5a6485", 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"de33abf4b62d471e8028c1008d4cbbf5", "e2cc4fd72cd44e0183b6c06a06769ede", "bfcd8fae5e3d4eb184d7b7381d18c7e6", "990b8e7b343941cd96723d0d888cfff1", "be391627d8024e0fb1414a8d29535f51", "fd58b4bfd6cf4f4c8def716a2b26158c", "9bdc6d1ae55e41c7a21da87693146975", "475372370d894563922de32472d4fb44", "0593664c5c564758baf6c1aec12e5359", "cb2dcf2a81144233bdc13df4cfe38e09", "f9b37a5e510740eeb4d17dc4aee5048e", "bcb57d4fea5b445a95558de4d85f06be", "1765a4552cc94ac0925270e6cbfed2c1", "d0a4c93e923b4326a6c8a1e3e950b5a9", "7f7ffd01cbc449df9e12b3a429be8bea", "fcb6231662db47beb2d802c8334fb64e", "1027abe320e845ef9165753103b95ef0", "0402c02af7b446a9905e1d3af4241688", "626f497768c3482eb549417911d6902e", "c0825eaa869643558899fff4bd1688bc", "3e9e4049ebd84b23ab9b10acf6c7a07b", "44982307de884a559d72470f5ea5b347", "632ce018f391422da2262e9ae3c47994", "36739b46ca764b299d13df03b6c24e37", "65282667351d4520934c1dddf0a97d08", "8fc31e9dd1fe4aea80b255dba9ba38b1", "4efa1543c89c4a38af52971a28aa86cf", "e00b4deeb09e4f9bbe69cfac15451e46", "f44da593fb9b4269bb44a229a4b05368", "da4e4db8f92d48a49443c05a4b4b648f", "058a63cf793f477b91f184c1063d82f4" ] }, "id": "YJ4YoJzs-3r3", "outputId": "9835592e-17f9-4177-d2d5-7c06f451a59d" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "0it [00:00, ?it/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "fbc875d5c41840659d62ace56a25061c" } }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "🦥 Unsloth Zoo will now patch everything to make training faster!\n", "==((====))== Unsloth 2025.1.6: Fast Gemma2 patching. Transformers: 4.47.1.\n", " \\\\ /| GPU: NVIDIA A100-SXM4-40GB. Max memory: 39.564 GB. Platform: Linux.\n", "O^O/ \\_/ \\ Torch: 2.5.1+cu121. CUDA: 8.0. CUDA Toolkit: 12.1. Triton: 3.1.0\n", "\\ / Bfloat16 = TRUE. FA [Xformers = 0.0.29.post1. FA2 = True]\n", " \"-____-\" Free Apache license: http://github.com/unslothai/unsloth\n", "Unsloth: Fast downloading is enabled - ignore downloading bars which are red colored!\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "model.safetensors.index.json: 0%| | 0.00/39.1k [00:00\n", "
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1चेन्नई में लोकप्रिय व्यंजन कौन से हैं? ### लंब...डोसा, इडली, चावल, मिठाई।hiNaNNaNNaNNaN
2A student has to obtain 60% of the total marks...Let's denote the maximum marks as M.\\n\\nTo pas...enNaNNaNNaNNaN
3Karwar Style Ambade Udid Methi Recipe - Hog Pl...To begin making the Karwar Style Ambade Udid M...enNaNNaNNaNNaN
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........................
43385What role does tax policy play in the regulati...Tax policy plays a significant role in regulat...enNaNNaNNaNNaN
43386एक पायथन फ़ंक्शन लिखें जो दिए गए ऐरे से सबसे छ...def find_First_Missing(array,start,end): \\r\\n ...hiNaNNaNNaNNaN
43387\"How do gravitational waves affect the orbital...Gravitational waves are ripples in the fabric ...enNaNNaNGravitational wavesNaN
43388Plants need iron to grow. What parts of plants...AenNaNNaNNaNNaN
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Which of the following soil changes is due only to natural causes? ### ['A: degradation of nutrients due to pesticides', 'B: formation of deserts due to tree felling', 'C: flooding due to dam construction', 'D: removal of nutrients due to heavy rains'] ### MCQ ### \",\n \"Given a set of symptoms, provide a list of potential diagnoses that could explain the symptoms. ### Symptoms: Nausea, vomiting, abdominal pain, fever ### LONG RESPONSE ### \"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Output\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 23514,\n \"samples\": [\n \"To calculate the kinetic energy gained by a proton as it undergoes relativistic acceleration, we need to use the relativistic kinetic energy formula:\\n\\nK = (\\u03b3 - 1)mc^2\\n\\nwhere K is the kinetic energy, \\u03b3 (gamma) is the Lorentz factor, m is the rest mass of the proton, and c is the speed of light.\\n\\nFirst, we need to find the Lorentz factor (\\u03b3) using the formula:\\n\\n\\u03b3 = 1 / sqrt(1 - v^2/c^2)\\n\\nwhere v is the final speed of the proton (0.8c).\\n\\n\\u03b3 = 1 / sqrt(1 - (0.8c)^2/c^2)\\n\\u03b3 = 1 / sqrt(1 - 0.64)\\n\\u03b3 = 1 / sqrt(0.36)\\n\\u03b3 = 1 / 0.6\\n\\u03b3 \\u2248 1.667\\n\\nNow, we can calculate the kinetic energy:\\n\\nK = (\\u03b3 - 1)mc^2\\nK = (1.667 - 1)(1.67\\u00d710^-27 kg)(3\\u00d710^8 m/s)^2\\nK \\u2248 0.667 \\u00d7 1.67\\u00d710^-27 kg \\u00d7 9\\u00d710^16 m^2/s^2\\nK \\u2248 1.001 \\u00d7 10^-10 J\\n\\nSo, the kinetic energy gained by the proton is approximately 1.001 \\u00d7 10^-10 Joules.\",\n \"Cosmic rays are high-energy particles, primarily protons and atomic nuclei, originating from outer space. They constantly bombard the Earth and its atmosphere, and can also interact with satellite electronics in orbit. The effects of cosmic rays on satellite electronics can be detrimental, causing various issues such as:\\n\\n1. Single Event Effects (SEEs): Cosmic rays can cause temporary or permanent malfunctions in electronic components by depositing their energy in the semiconductor material. This can lead to single event upsets (SEUs), single event latch-ups (SELs), and single event burnouts (SEBs), which can disrupt the normal operation of the satellite.\\n\\n2. Total Ionizing Dose (TID): The cumulative ionizing radiation dose received by the satellite electronics over time can cause degradation of the semiconductor material, leading to performance issues and reduced lifetime of the components.\\n\\n3. Displacement Damage: Cosmic rays can displace atoms in the semiconductor lattice, causing defects that can affect the performance of electronic devices, such as increased leakage current and reduced carrier mobility.\\n\\nTo mitigate the effects of cosmic rays on satellite electronics, several strategies can be employed:\\n\\n1. Shielding: Using shielding materials, such as aluminum or polyethylene, can help absorb or deflect some of the incoming cosmic rays, reducing their impact on the electronics. However, this can also increase the satellite's mass, which may not be desirable.\\n\\n2. Radiation-hardened components: Designing and using radiation-hardened electronic components can help resist the effects of cosmic rays. These components are specifically designed to withstand the harsh radiation environment in space.\\n\\n3. Error detection and correction: Implementing error detection and correction techniques, such as parity checks and redundant systems, can help identify and correct errors caused by cosmic rays, ensuring the continued operation of the satellite.\\n\\n4. Redundancy: Incorporating redundant systems and components can help maintain the functionality of the satellite in case of a failure caused by cosmic rays. This can include using multiple identical components or having backup systems in place.\\n\\n5. Regular monitoring and maintenance: Continuously monitoring the performance of satellite electronics and conducting regular maintenance can help identify and address any issues caused by cosmic rays before they become critical.\\n\\nIn summary, cosmic rays can cause various issues in satellite electronics, affecting their function and performance. To mitigate these effects, a combination of shielding, radiation-hardened components, error detection and correction, redundancy, and regular monitoring and maintenance can be employed.\",\n \"Day 1: Marina Beach, Kapaleeshwarar Temple. Day 2: Mahabalipuram, Fort St. George. Day 3: Guindy National Park, DakshinaChitra. Day 4: Day of rest or local exploration. 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