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updates and fixes
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‎Fine_tune_PaliGemma.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "EB0gv8OzHfLV",
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"outputId": "9de07e75-ddf4-4347-fc41-432a23774e2c"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
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" Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
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" Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m480.6/480.6 kB\u001b[0m \u001b[31m25.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m69.1/69.1 MB\u001b[0m \u001b[31m28.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m7.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m179.3/179.3 kB\u001b[0m \u001b[31m14.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m8.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.0/3.0 MB\u001b[0m \u001b[31m75.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.1/194.1 kB\u001b[0m \u001b[31m17.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[?25h Building wheel for transformers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
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"\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",
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"gcsfs 2024.10.0 requires fsspec==2024.10.0, but you have fsspec 2024.9.0 which is incompatible.\u001b[0m\u001b[31m\n",
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"\u001b[0m"
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]
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}
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],
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"!pip install -q -U datasets bitsandbytes peft git+https://github.com/huggingface/transformers.git"
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]
@@ -68,53 +41,9 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 17,
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"referenced_widgets": [
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"5515d96f0c8947f0ad4b7f17eb7d63f6",
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"d703de12cf9d4f87aa6ec2cc52f1090a",
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"757bc788bd6842d28a9f889187ffb88e",
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]
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},
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"id": "NzJZSHD8tZZy",
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"outputId": "c01b2b6f-3c1e-45da-9fc0-f4f518bcca24"
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},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "4f0e85aa740146d3aca81588a0288031",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from huggingface_hub import notebook_login\n",
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"notebook_login()"
@@ -131,31 +60,12 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "az5kdSbNpjgH",
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"outputId": "2d9f379c-eb31-45b0-b84c-79c2a2577d01"
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},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
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"The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
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"To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
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"You will be able to reuse this secret in all of your notebooks.\n",
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"Please note that authentication is recommended but still optional to access public models or datasets.\n",
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" warnings.warn(\n"
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]
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}
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],
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from datasets import load_dataset\n",
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"ds = load_dataset('merve/vqav2-small', split=\"validation\")\n"
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"ds = load_dataset('merve/vqav2-small', split=\"validation\")"
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]
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},
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{

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