fix(docs): Correct typos in Gemma_2 notebooks

Author: Rahul-Lashkari

Gemma/[Gemma_2]Aligning_DPO.ipynb

@@ -40,7 +40,7 @@
         "# Aligning with DPO a Gemma-2 2B model.\n",
         "by [Pere Martra](https://github.com/peremartra)\n",
         "\n",
-        "This notebook demostrates how to align a Gemma-2 model using DPO (Direct Preference Optimization).\n",
+        "This notebook demonstrates how to align a Gemma-2 model using DPO (Direct Preference Optimization).\n",
         "<table align=\"left\">\n",
         "  <td>\n",
         "    <a target=\"_blank\" href=\"https://colab.research.google.com/github/google-gemini/gemma-cookbook/blob/main/Gemma/[Gemma_2]Aligning_DPO.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n",

Gemma/[Gemma_2]Custom_Vocabulary.ipynb

@@ -41,7 +41,7 @@
         "\n",
         "This notebook demonstrates how to use a custom vocabulary in Gemma.\n",
         "\n",
-        "Consider a document containing a length word, such as \"MyCustomWordInMyDocument\" with a high frequency of occurrence. It will be fragmented into several tokens, resulting in inefficiencies. Gemma Tokenizer offeres a potential solution in the form of \"<unused[0-98]>\" tokens. However, this approach requires additional training, as the base model lacks knowledge of these tokens.\n",
+        "Consider a document containing a length word, such as \"MyCustomWordInMyDocument\" with a high frequency of occurrence. It will be fragmented into several tokens, resulting in inefficiencies. Gemma Tokenizer offers a potential solution in the form of \"<unused[0-98]>\" tokens. However, this approach requires additional training, as the base model lacks knowledge of these tokens.\n",
         "\n",
         "In this demo, you will fine-tune the model with a simple prompt \"日本の珍しい名字\" which means \"Rare Japanese surnames\".\n",
         "\n",

Gemma/[Gemma_2]Finetune_with_Axolotl.ipynb

@@ -39,7 +39,7 @@
       "source": [
         "# Gemma - finetune with Axolotl\n",
         "\n",
-        "This notebook demonstrates how to finetune Gemma with Axolotl. [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) is is a tool designed to streamline the fine-tuning of various AI models, offering support for multiple configurations and architectures. Axolotl wraps the Hugging Face finetuning functionality and provides a simple interface for finetuning.\n",
+        "This notebook demonstrates how to finetune Gemma with Axolotl. [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) is a tool designed to streamline the fine-tuning of various AI models, offering support for multiple configurations and architectures. Axolotl wraps the Hugging Face finetuning functionality and provides a simple interface for finetuning.\n",
         "It's very easy to finetune Gemma with Axolotl. This notebook follows the [official Colab notebook](https://github.com/OpenAccess-AI-Collective/axolotl/blob/main/examples/colab-notebooks/colab-axolotl-example.ipynb) closely.\n",
         "\n",
         "<table align=\"left\">\n",

Gemma/[Gemma_2]Finetune_with_JORA.ipynb

@@ -985,7 +985,7 @@
       "source": [
         "generate_response(\n",
         "    instruction=\"Identify 3 common mistakes in the following sentence. Suggest changes.\",\n",
-        "    input_text=\"She seems to believe that the real key to sucsess is working smart and hard.\"\n",
+        "    input_text=\"She seems to believe that the real key to success is working smart and hard.\"\n",
         ")"
       ]
     },

Gemma/[Gemma_2]Finetune_with_LitGPT.ipynb

@@ -2006,7 +2006,7 @@
       ],
       "source": [
         "!litgpt generate $FINETUNED_MODEL_DIR/final \\\n",
-        "  --prompt \"Generate the next number in the Fibonnaci series: 1, 1, 2, 3, 5\""
+        "  --prompt \"Generate the next number in the Fibonacci series: 1, 1, 2, 3, 5\""
       ]
     },
     {
@@ -2109,7 +2109,7 @@
         "from litgpt import prompts\n",
         "\n",
         "alpaca_prompt_style = prompts.Alpaca()\n",
-        "prompt_text = alpaca_prompt_style.apply(prompt=\"Generate the next number in the Fibonnaci series.\",\n",
+        "prompt_text = alpaca_prompt_style.apply(prompt=\"Generate the next number in the Fibonacci series.\",\n",
         "                                        input=\"1, 1, 2, 3, 5, 8\")\n",
         "print(prompt_text)"
       ]

Gemma/[Gemma_2]LangChain_chaining.ipynb

@@ -83,7 +83,7 @@
       "source": [
         "### Configure your credentials\n",
         "\n",
-        "Add your your Kaggle credentials to the Colab Secrets manager to securely store it.\n",
+        "Add your Kaggle credentials to the Colab Secrets manager to securely store it.\n",
         "\n",
         "1. Open your Google Colab notebook and click on the 🔑 Secrets tab in the left panel. <img src=\"https://storage.googleapis.com/generativeai-downloads/images/secrets.jpg\" alt=\"The Secrets tab is found on the left panel.\" width=50%>\n",
         "2. Create new secrets: `KAGGLE_USERNAME` and `KAGGLE_KEY`\n",

Gemma/[Gemma_2]evaluation.ipynb

@@ -78,7 +78,7 @@
       "source": [
         "### Configure your credentials\n",
         "\n",
-        "Add your your Kaggle credentials to the Colab Secrets manager to securely store it.\n",
+        "Add your Kaggle credentials to the Colab Secrets manager to securely store it.\n",
         "\n",
         "1. Open your Google Colab notebook and click on the 🔑 Secrets tab in the left panel. <img src=\"https://storage.googleapis.com/generativeai-downloads/images/secrets.jpg\" alt=\"The Secrets tab is found on the left panel.\" width=50%>\n",
         "2. Create new secrets: `KAGGLE_USERNAME` and `KAGGLE_KEY`\n",

Gemma/[Gemma_2]on_Groq.ipynb

@@ -39,7 +39,7 @@
       "source": [
         "# Gemma 2 running on Groq\n",
         "\n",
-        "This cookbook shows how to call the Gemma 2 9B IT model hosted on [Groq Cloud](https://console.groq.com/). Groq is an AI accelerater company that provides [free Gemma 2 9B access](https://console.groq.com/docs/models) with blazing fast inference speed.\n",
+        "This cookbook shows how to call the Gemma 2 9B IT model hosted on [Groq Cloud](https://console.groq.com/). Groq is an AI accelerator company that provides [free Gemma 2 9B access](https://console.groq.com/docs/models) with blazing fast inference speed.\n",
         "\n",
         "<table align=\"left\">\n",
         "  <td>\n",