Updated mistral.rs notebook documentation

Gemma/Using_Gemma_with_mistral_rs.ipynb

@@ -42,7 +42,7 @@
         "[Gemma](https://ai.google.dev/gemma) is a family of lightweight, state-of-the-art open-source language models from Google. Built from the same research and technology used to create the Gemini models, Gemma models are text-to-text, decoder-only large language models (LLMs), available in English, with open weights, pre-trained variants, and instruction-tuned variants.\n",
         "Gemma models are well-suited for various text-generation tasks, including question-answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as a laptop, desktop, or your cloud infrastructure, democratizing access to state-of-the-art AI models and helping foster innovation for everyone.\n",
         "\n",
-        "[mistral.rs](https://github.com/EricLBuehler/mistral.rs) is a versatile framework for Large Language Model (LLM) inference supporting text-text and multimodal LLMs. It offers features like grammar support for structured outputs, and inference using LoRA-fine-tuned models, making it a powerful tool for a wide range of AI applications.\n",
+        "[mistral.rs](https://github.com/EricLBuehler/mistral.rs) is a versatile framework for Large Language Model (LLM) inference supporting text-to-text and multimodal LLMs. It offers features like grammar support for structured outputs, and inference using LoRA-fine-tuned models, making it a powerful tool for a wide range of AI applications.\n",
         "\n",
         "In this notebook, you will learn how to prompt the Gemma 2 model in various ways using the **mistral.rs** Python APIs in a Google Colab environment.\n",
         "<table align=\"left\">\n",