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nbfmt gemma site notebooks (#508)
This ensures notebook diffs are simple and consistent.
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‎site/en/gemma/docs/codegemma/codegemma_flax_inference.ipynb‎

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"source": [
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"<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
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" <td>\n",
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" <a target=\"_blank\" href=\"https://ai.google.dev/gemma/docs/codegemma/keras_quickstart\"><img src=\"https://ai.google.dev/static/site-assets/images/docs/notebook-site-button.png\" height=\"32\" width=\"32\" />View on ai.google.dev</a>\n",
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" <a target=\"_blank\" href=\"https://ai.google.dev/gemma/docs/codegemma/codegemma_flax_inference\"><img src=\"https://ai.google.dev/static/site-assets/images/docs/notebook-site-button.png\" height=\"32\" width=\"32\" />View on ai.google.dev</a>\n",
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" </td>\n",
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" <td>\n",
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" <a target=\"_blank\" href=\"https://colab.research.google.com/github/google/generative-ai-docs/blob/main/site/en/gemma/docs/codegemma/flax_quickstart.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n",
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" <a target=\"_blank\" href=\"https://colab.research.google.com/github/google/generative-ai-docs/blob/main/site/en/gemma/docs/codegemma/codegemma_flax_inference.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n",
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" </td>\n",
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" <td>\n",
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" <a target=\"_blank\" href=\"https://github.com/google/generative-ai-docs/blob/main/site/en/gemma/docs/codegemma/flax_quickstart.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />View source on GitHub</a>\n",
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" <a target=\"_blank\" href=\"https://github.com/google/generative-ai-docs/blob/main/site/en/gemma/docs/codegemma/codegemma_flax_inference.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />View source on GitHub</a>\n",
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" </td>\n",
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"</table>"
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]
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"cell_type": "code",
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"execution_count": null,
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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": "XpSw-_4EEcoY",
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"outputId": "ff9d2cab-80e1-4e5f-b976-94769cd3e730"
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"id": "XpSw-_4EEcoY"
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"outputs": [
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{
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"cell_type": "code",
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"execution_count": null,
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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": "j_QdPAGyO5zl",
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"outputId": "8181d17f-da02-4d1b-ce34-cbd048362007"
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"id": "j_QdPAGyO5zl"
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},
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"outputs": [
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{
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"cell_type": "code",
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"execution_count": null,
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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": "cjnXlLkWcHIy",
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"outputId": "79cfb87d-fef7-4eb5-f452-48294c352bd6"
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"id": "cjnXlLkWcHIy"
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"outputs": [
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{
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"cell_type": "code",
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"execution_count": null,
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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": "JAwXvpzbuiB5",
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"outputId": "b526c792-1105-47ea-932d-3c8d3a1919bc"
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"id": "JAwXvpzbuiB5"
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"outputs": [
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{
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"cell_type": "code",
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"execution_count": null,
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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": "TpyG5YW1EcoY",
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"outputId": "be890773-f521-45a5-d379-4036c9cbb3de"
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"id": "TpyG5YW1EcoY"
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},
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"outputs": [
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{
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"cell_type": "code",
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"execution_count": null,
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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": "S5F3fk22Ecod",
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"id": "S5F3fk22Ecod"
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"outputs": [
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{
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"cell_type": "code",
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"execution_count": null,
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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": "6zIQEruE5_FC",
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"outputId": "29e4e090-fd05-432d-ca13-bbc42443b958"
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"id": "6zIQEruE5_FC"
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"outputs": [
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{
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"cell_type": "code",
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"execution_count": null,
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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": "SvaV4GU76M3t",
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"outputId": "76d55cf4-a586-4faa-cb8a-7968b7e8ada0"
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"id": "SvaV4GU76M3t"
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"outputs": [
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{
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"metadata": {
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"accelerator": "TPU",
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"colab": {
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"gpuType": "V28",
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"provenance": []
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"name": "codegemma_flax_inference.ipynb",
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"toc_visible": true
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},
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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"name": "python"
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‎site/en/gemma/docs/paligemma/fine-tuning-paligemma.ipynb‎

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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"cellView": "form",
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"id": "_fEE8rM9BUfS"
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"outputs": [],
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"source": [
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"# Fine-tune PaliGemma with JAX and Flax\n",
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"\n",
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"\u003ctable class=\"tfo-notebook-buttons\" align=\"left\"\u003e\n",
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"\u003ctd\u003e\n",
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"\u003ca target=\"_blank\" href=\"https://ai.google.dev/gemma/docs/paligemma/fine-tuning-paligemma\"\u003e\u003cimg src=\"https://ai.google.dev/static/site-assets/images/docs/notebook-site-button.png\" height=\"32\" width=\"32\" /\u003eView on ai.google.dev\u003c/a\u003e\n",
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"\u003c/td\u003e\n",
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"\u003ctd\u003e\n",
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"\u003ca target=\"_blank\" href=\"https://colab.research.google.com/github/google/generative-ai-docs/blob/main/site/en/gemma/docs/paligemma/fine-tuning-paligemma.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /\u003eRun in Google Colab\u003c/a\u003e\n",
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"\u003c/td\u003e\n",
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"\u003ctd\u003e\n",
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"\u003ca target=\"_blank\" href=\"https://github.com/google/generative-ai-docs/blob/main/site/en/gemma/docs/paligemma/fine-tuning-paligemma.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /\u003eView source on GitHub\u003c/a\u003e\n",
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"\u003c/td\u003e\n",
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"\u003c/table\u003e\n"
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"<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
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"<td>\n",
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"<a target=\"_blank\" href=\"https://ai.google.dev/gemma/docs/paligemma/fine-tuning-paligemma\"><img src=\"https://ai.google.dev/static/site-assets/images/docs/notebook-site-button.png\" height=\"32\" width=\"32\" />View on ai.google.dev</a>\n",
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"</td>\n",
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"<td>\n",
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"<a target=\"_blank\" href=\"https://colab.research.google.com/github/google/generative-ai-docs/blob/main/site/en/gemma/docs/paligemma/fine-tuning-paligemma.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n",
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"</td>\n",
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"<td>\n",
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"<a target=\"_blank\" href=\"https://github.com/google/generative-ai-docs/blob/main/site/en/gemma/docs/paligemma/fine-tuning-paligemma.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />View source on GitHub</a>\n",
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"</td>\n",
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"</table>\n"
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]
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},
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{
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"\n",
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"To generate a Kaggle API key, open your [**Settings** page in Kaggle](https://www.kaggle.com/settings) and click **Create New Token**. This triggers the download of a `kaggle.json` file containing your API credentials.\n",
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"\n",
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"Then, in Colab, select **Secrets** (🔑) in the left pane and add your Kaggle username and Kaggle API key. Store your username under the name `KAGGLE_USERNAME` and your API key under the name `KAGGLE_KEY`.\n",
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"\n"
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"Then, in Colab, select **Secrets** (🔑) in the left pane and add your Kaggle username and Kaggle API key. Store your username under the name `KAGGLE_USERNAME` and your API key under the name `KAGGLE_KEY`.\n"
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]
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{
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"\n",
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" image = tf.constant(image)\n",
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" image = tf.image.resize(image, (size, size), method='bilinear', antialias=True)\n",
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" return image.numpy() / 127.5 - 1.0 # [0, 255]-\u003e[-1,1]\n",
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" return image.numpy() / 127.5 - 1.0 # [0, 255]->[-1,1]\n",
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"\n",
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"def preprocess_tokens(prefix, suffix=None, seqlen=None):\n",
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" # Model has been trained to handle tokenized text composed of a prefix with\n",
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" return f\"data:image/jpeg;base64,{image_b64}\"\n",
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"\n",
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"def render_example(image, caption):\n",
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" image = ((image + 1)/2 * 255).astype(np.uint8) # [-1,1] -\u003e [0, 255]\n",
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" image = ((image + 1)/2 * 255).astype(np.uint8) # [-1,1] -> [0, 255]\n",
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" return f\"\"\"\n",
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" \u003cdiv style=\"display: inline-flex; align-items: center; justify-content: center;\"\u003e\n",
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" \u003cimg style=\"width:128px; height:128px;\" src=\"{render_inline(image, resize=(64,64))}\" /\u003e\n",
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" \u003cp style=\"width:256px; margin:10px; font-size:small;\"\u003e{html.escape(caption)}\u003c/p\u003e\n",
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" \u003c/div\u003e\n",
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" <div style=\"display: inline-flex; align-items: center; justify-content: center;\">\n",
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" <img style=\"width:128px; height:128px;\" src=\"{render_inline(image, resize=(64,64))}\" />\n",
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" <p style=\"width:256px; margin:10px; font-size:small;\">{html.escape(caption)}</p>\n",
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" </div>\n",
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"html_out = \"\"\n",
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" # Append to html output.\n",
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" for example, response in zip(examples, responses):\n",
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" if num_examples and len(outputs) \u003e= num_examples:\n",
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" if num_examples and len(outputs) >= num_examples:\n",
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" return outputs"
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],
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"metadata": {
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"colab": {
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"gpuType": "T4",
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"last_runtime": {
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"build_target": "//learning/grp/tools/ml_python:ml_notebook",
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"kind": "private"
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},
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"private_outputs": true,
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"provenance": [
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{
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"file_id": "17AiK8gRY7oiquQGkBH0d08PFQo3Kyx1I",
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"timestamp": 1715287187925
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},
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{
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"file_id": "1qZlJfPyfKRrNcz2shxQ93HnnE5Ge1LLn",
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"timestamp": 1715019972450
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},
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{
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"file_id": "1JFnlD2kSiTNexdPw_NYRtuW6uuSTI0kD",
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"timestamp": 1714585741026
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}
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],
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"name": "fine-tuning-paligemma.ipynb",
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"toc_visible": true
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},
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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"language_info": {
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"name": "python"
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"nbformat": 4,

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