diff --git a/docs/examples/Supported_Models.ipynb b/docs/examples/Supported_Models.ipynb
index d52a98fc..654f5a3f 100644
--- a/docs/examples/Supported_Models.ipynb
+++ b/docs/examples/Supported_Models.ipynb
@@ -2,9 +2,18 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/homebrew/Caskroom/miniconda/base/envs/fst/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n",
+      "\u001b[32m2024-02-15 12:52:09.386\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mfastembed.embedding\u001b[0m:\u001b[36m<module>\u001b[0m:\u001b[36m7\u001b[0m - \u001b[33m\u001b[1mDefaultEmbedding, FlagEmbedding, JinaEmbedding are deprecated. Use TextEmbedding instead.\u001b[0m\n"
+     ]
+    },
     {
      "data": {
       "text/html": [
@@ -76,6 +85,14 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
+       "      <td>nomic-ai/nomic-embed-text-v1</td>\n",
+       "      <td>768</td>\n",
+       "      <td>8192 context length english model</td>\n",
+       "      <td>0.54</td>\n",
+       "      <td>{'hf': 'nomic-ai/nomic-embed-text-v1'}</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
        "      <td>intfloat/multilingual-e5-large</td>\n",
        "      <td>1024</td>\n",
        "      <td>Multilingual model, e5-large. Recommend using this model for non-English languages</td>\n",
@@ -83,7 +100,7 @@
        "      <td>{'url': 'https://storage.googleapis.com/qdrant-fastembed/fast-multilingual-e5-large.tar.gz', 'hf': 'qdrant/multilingual-e5-large-onnx'}</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>6</th>\n",
+       "      <th>7</th>\n",
        "      <td>sentence-transformers/paraphrase-multilingual-mpnet-base-v2</td>\n",
        "      <td>768</td>\n",
        "      <td>Sentence-transformers model for tasks like clustering or semantic search</td>\n",
@@ -91,7 +108,7 @@
        "      <td>{'hf': 'xenova/paraphrase-multilingual-mpnet-base-v2'}</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>7</th>\n",
+       "      <th>8</th>\n",
        "      <td>jinaai/jina-embeddings-v2-base-en</td>\n",
        "      <td>768</td>\n",
        "      <td>English embedding model supporting 8192 sequence length</td>\n",
@@ -99,7 +116,7 @@
        "      <td>{'hf': 'xenova/jina-embeddings-v2-base-en'}</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
+       "      <th>9</th>\n",
        "      <td>jinaai/jina-embeddings-v2-small-en</td>\n",
        "      <td>512</td>\n",
        "      <td>English embedding model supporting 8192 sequence length</td>\n",
@@ -117,10 +134,11 @@
        "2                                       BAAI/bge-small-en-v1.5   384   \n",
        "3                                       BAAI/bge-small-zh-v1.5   512   \n",
        "4                       sentence-transformers/all-MiniLM-L6-v2   384   \n",
-       "5                               intfloat/multilingual-e5-large  1024   \n",
-       "6  sentence-transformers/paraphrase-multilingual-mpnet-base-v2   768   \n",
-       "7                            jinaai/jina-embeddings-v2-base-en   768   \n",
-       "8                           jinaai/jina-embeddings-v2-small-en   512   \n",
+       "5                                 nomic-ai/nomic-embed-text-v1   768   \n",
+       "6                               intfloat/multilingual-e5-large  1024   \n",
+       "7  sentence-transformers/paraphrase-multilingual-mpnet-base-v2   768   \n",
+       "8                            jinaai/jina-embeddings-v2-base-en   768   \n",
+       "9                           jinaai/jina-embeddings-v2-small-en   512   \n",
        "\n",
        "                                                                          description  \\\n",
        "0                                                            Base English model, v1.5   \n",
@@ -128,10 +146,11 @@
        "2                                                      Fast and Default English model   \n",
        "3                                                  Fast and recommended Chinese model   \n",
        "4                                            Sentence Transformer model, MiniLM-L6-v2   \n",
-       "5  Multilingual model, e5-large. Recommend using this model for non-English languages   \n",
-       "6            Sentence-transformers model for tasks like clustering or semantic search   \n",
-       "7                             English embedding model supporting 8192 sequence length   \n",
+       "5                                                   8192 context length english model   \n",
+       "6  Multilingual model, e5-large. Recommend using this model for non-English languages   \n",
+       "7            Sentence-transformers model for tasks like clustering or semantic search   \n",
        "8                             English embedding model supporting 8192 sequence length   \n",
+       "9                             English embedding model supporting 8192 sequence length   \n",
        "\n",
        "   size_in_GB  \\\n",
        "0        0.44   \n",
@@ -139,10 +158,11 @@
        "2        0.13   \n",
        "3        0.10   \n",
        "4        0.09   \n",
-       "5        2.24   \n",
-       "6        1.11   \n",
-       "7        0.55   \n",
-       "8        0.13   \n",
+       "5        0.54   \n",
+       "6        2.24   \n",
+       "7        1.11   \n",
+       "8        0.55   \n",
+       "9        0.13   \n",
        "\n",
        "                                                                                                                                          sources  \n",
        "0                 {'url': 'https://storage.googleapis.com/qdrant-fastembed/fast-bge-base-en-v1.5.tar.gz', 'hf': 'qdrant/bge-base-en-v1.5-onnx-q'}  \n",
@@ -150,13 +170,14 @@
        "2               {'url': 'https://storage.googleapis.com/qdrant-fastembed/fast-bge-small-en-v1.5.tar.gz', 'hf': 'qdrant/bge-small-en-v1.5-onnx-q'}  \n",
        "3                                                        {'url': 'https://storage.googleapis.com/qdrant-fastembed/fast-bge-small-zh-v1.5.tar.gz'}  \n",
        "4  {'url': 'https://storage.googleapis.com/qdrant-fastembed/sentence-transformers-all-MiniLM-L6-v2.tar.gz', 'hf': 'qdrant/all-MiniLM-L6-v2-onnx'}  \n",
-       "5         {'url': 'https://storage.googleapis.com/qdrant-fastembed/fast-multilingual-e5-large.tar.gz', 'hf': 'qdrant/multilingual-e5-large-onnx'}  \n",
-       "6                                                                                          {'hf': 'xenova/paraphrase-multilingual-mpnet-base-v2'}  \n",
-       "7                                                                                                     {'hf': 'xenova/jina-embeddings-v2-base-en'}  \n",
-       "8                                                                                                    {'hf': 'xenova/jina-embeddings-v2-small-en'}  "
+       "5                                                                                                          {'hf': 'nomic-ai/nomic-embed-text-v1'}  \n",
+       "6         {'url': 'https://storage.googleapis.com/qdrant-fastembed/fast-multilingual-e5-large.tar.gz', 'hf': 'qdrant/multilingual-e5-large-onnx'}  \n",
+       "7                                                                                          {'hf': 'xenova/paraphrase-multilingual-mpnet-base-v2'}  \n",
+       "8                                                                                                     {'hf': 'xenova/jina-embeddings-v2-base-en'}  \n",
+       "9                                                                                                    {'hf': 'xenova/jina-embeddings-v2-small-en'}  "
       ]
      },
-     "execution_count": 4,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }