Update model names (#434)

google · May 24, 2024 · 695b0fd · 695b0fd
1 parent 1827b09
commit 695b0fd
Showing 1 changed file with 13 additions and 22 deletions.
diff --git a/site/en/gemini-api/docs/get-started/python.ipynb b/site/en/gemini-api/docs/get-started/python.ipynb
@@ -231,8 +231,8 @@
         "\n",
         "Now you're ready to call the Gemini API. Use `list_models` to see the available Gemini models:\n",
         "\n",
-        "* `gemini-pro`: optimized for text-only prompts.\n",
-        "* `gemini-pro-vision`: optimized for text-and-images prompts."
+        "* `gemini-1.5-pro`: optimized for high intelligence tasks, the most powerful Gemini model\n",
+        "* `gemini-1.5-flash`: optimized for multi-modal use-cases where speed and cost are important"
       ]
     },
     {
@@ -278,7 +278,7 @@
       },
       "outputs": [],
       "source": [
-        "model = genai.GenerativeModel('gemini-pro')"
+        "model = genai.GenerativeModel('gemini-1.5-flash')"
       ]
     },
     {
@@ -712,7 +712,7 @@
         "id": "7r99TN2R8EUD"
       },
       "source": [
-        "Use the `gemini-pro-vision` model and pass the image to the model with `generate_content`."
+        "Use the `gemini-1.5-flash` model and pass the image to the model with `generate_content`."
       ]
     },
     {
@@ -723,7 +723,7 @@
       },
       "outputs": [],
       "source": [
-        "model = genai.GenerativeModel('gemini-pro-vision')"
+        "model = genai.GenerativeModel('gemini-1.5-flash')"
       ]
     },
     {
@@ -839,20 +839,11 @@
         }
       ],
       "source": [
-        "model = genai.GenerativeModel('gemini-pro')\n",
+        "model = genai.GenerativeModel('gemini-1.5-flash')\n",
         "chat = model.start_chat(history=[])\n",
         "chat"
       ]
     },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "88Il02N-km9j"
-      },
-      "source": [
-        "Note: The vision model `gemini-pro-vision` is not optimized for multi-turn chat."
-      ]
-    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -1139,7 +1130,7 @@
       ],
       "source": [
         "result = genai.embed_content(\n",
-        "    model=\"models/embedding-001\",\n",
+        "    model=\"models/text-embedding-004\",\n",
         "    content=\"What is the meaning of life?\",\n",
         "    task_type=\"retrieval_document\",\n",
         "    title=\"Embedding of single string\")\n",
@@ -1178,7 +1169,7 @@
       ],
       "source": [
         "result = genai.embed_content(\n",
-        "    model=\"models/embedding-001\",\n",
+        "    model=\"models/text-embedding-004\",\n",
         "    content=[\n",
         "      'What is the meaning of life?',\n",
         "      'How much wood would a woodchuck chuck?',\n",
@@ -1244,7 +1235,7 @@
       ],
       "source": [
         "result = genai.embed_content(\n",
-        "    model = 'models/embedding-001',\n",
+        "    model = 'models/text-embedding-004',\n",
         "    content = response.candidates[0].content)\n",
         "\n",
         "# 1 input > 1 vector output\n",
@@ -1317,7 +1308,7 @@
       ],
       "source": [
         "result = genai.embed_content(\n",
-        "    model = 'models/embedding-001',\n",
+        "    model = 'models/text-embedding-004',\n",
         "    content = chat.history)\n",
         "\n",
         "# 1 input > 1 vector output\n",
@@ -1537,7 +1528,7 @@
       },
       "outputs": [],
       "source": [
-        "model = genai.GenerativeModel('gemini-pro-vision')\n",
+        "model = genai.GenerativeModel('gemini-1.5-flash')\n",
         "response = model.generate_content(\n",
         "    glm.Content(\n",
         "        parts = [\n",
@@ -1631,7 +1622,7 @@
         }
       ],
       "source": [
-        "model = genai.GenerativeModel('gemini-pro')\n",
+        "model = genai.GenerativeModel('gemini-1.5-flash')\n",
         "\n",
         "messages = [\n",
         "    {'role':'user',\n",
@@ -1754,7 +1745,7 @@
       },
       "outputs": [],
       "source": [
-        "model = genai.GenerativeModel('gemini-pro')\n",
+        "model = genai.GenerativeModel('gemini-1.5-flash')\n",
         "response = model.generate_content(\n",
         "    'Tell me a story about a magic backpack.',\n",
         "    generation_config=genai.types.GenerationConfig(\n",