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mhart/embeddinggemma-shortness.ipynb

Created September 8, 2025 09:51
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embeddinggemma-shortness.ipynb
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embeddinggemma-shortness.ipynb
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"<a href=\"https://colab.research.google.com/gist/mhart/71baa6614c0de04a2837542a57e29337/embeddinggemma-shortness.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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{
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"source": [
"## embeddinggemma prefers shorter content over more relevant content?\n",
"Model page: https://huggingface.co/google/embeddinggemma-300m\n",
"\n",
"An example of issues where embeddinggemma appears to prefer shorter content.\n",
"\n",
"**Is there some sort of padding issue going on? ie, padding tokens are causing the matching to be higher than just more tokens on the same topic?**"
],
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},
{
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"The model you are trying to use is gated. Please make sure you have access to it by visiting the model page.To run inference, either set HF_TOKEN in your environment variables/ Secrets or run the following cell to login. 🤗"
],
"metadata": {
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"outputId": "55307d57-273a-434f-c3cb-cb88def1b27a"
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{
"cell_type": "code",
"source": [
"# The first Queues Getting Started document is clearly the most relevant – but it's longer and has actual content about how to get started\n",
"# But the other three documents all score higher, even though they've got nothing to do with Queues\n",
"\n",
"# This happens with other documents and queries too\n",
"\n",
"docs = model.encode([\n",
" \"title: Queues · Getting started | text: Cloudflare Queues is a flexible messaging queue that allows you to queue messages for asynchronous processing. By following this guide, you will create your first queue, a Worker to publish messages to that queue, and a consumer Worker to consume messages from that queue.\\n\\n## Prerequisites\\n\\nTo use Queues, you will need:\\n\\n1. Sign up for a [Cloudflare account](https://dash.cloudflare.com/sign-up/workers-and-pages).\\n2. Install [`Node.js`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm).\\n\\n### Node.js version manager\\n\\nUse a Node version manager like [Volta](https://volta.sh/) or [nvm](https://github.com/nvm-sh/nvm) to avoid permission issues and change Node.js versions. [Wrangler](/workers/wrangler/install-and-update/), discussed later in this guide, requires a Node version of `16.17.0` or later.\\n\\n## 1. Create a Worker project\\n\\nYou will access your queue from a Worker, the producer Worker. You must create at least one producer Worker to publish messages onto your queue. If you are using [R2 Bucket Event Notifications](/r2/buckets/event-notifications/), then you do not need a producer Worker.\\n\\nTo create a producer Worker, run:\\n\\n```sh\\nnpm create cloudflare@latest -- \\\"producer-worker\\n```\\n\\nThis will create a new directory, which will include both a `src/index.ts` Worker script, and a [`wrangler.jsonc`](/workers/wrangler/configuration/) configuration file. After you create your Worker, you will create a Queue to access.\\n\\nMove into the newly created directory:\\n\\n```sh\\ncd producer-worker\\n```\\n\\n## 2. Create a queue\\n\\nTo use queues, you need to create at least one queue to publish messages to and consume messages from.\\n\\nTo create a queue, run:\\n\\n```sh\\nnpx wrangler queues create \\u003CMY-QUEUE-NAME\\u003E\\n```\\n\",\n",
" \"title: Web3 · Ethereum Gateway · Concepts | text: As you get started with Cloudflare's Ethereum Gateway, you may want to read through the following concepts.\\n\\n:::note\\n\\nFor help with additional concepts, refer to the [Ethereum documentation](https://ethereum.org/).\\n:::\",\n",
" \"title: Load Balancing · Get started | text: Get started with load balancing in one of two ways:\\n\\n* [Quickstart](/load-balancing/get-started/quickstart/): Get up and running quickly with Load Balancing.\\n* [Learning path](/learning-paths/load-balancing/concepts/): Check an in-depth walkthrough for how to plan and set up a load balancer.\",\n",
" \"title: Workers · Tutorials · Build a Slackbot | text: If you want to get started building your own projects, review the existing list of [Quickstart templates](/workers/get-started/quickstarts/).\",\n",
"])\n",
"\n",
"query = \"How do I get started with Queues?\"\n",
"\n",
"print(model.similarity(docs, model.encode([f\"task: search result | query: {query}\"])))\n",
"\n",
"print(model.similarity(docs, model.encode([f\"task: question answering | query: {query}\"])))\n",
"\n",
"# tensor([[0.4166],\n",
"# [0.4299],\n",
"# [0.4668],\n",
"# [0.4799]])\n",
"# tensor([[0.3731],\n",
"# [0.4365],\n",
"# [0.4623],\n",
"# [0.4645]])"
],
"metadata": {
"id": "cjVMrSRSRH99",
"outputId": "e302e956-63cf-4103-d159-bbc5444d80c0",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"tensor([[0.4166],\n",
" [0.4299],\n",
" [0.4668],\n",
" [0.4799]])\n",
"tensor([[0.3731],\n",
" [0.4365],\n",
" [0.4623],\n",
" [0.4645]])\n"
]
}
]
}
]
}
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