doc: update overview tb

Author: dsdanielpark

README.md

@@ -574,9 +574,9 @@ If you want to develop your own simple code, you can start from [this simple cod
 If you have sufficient GPU resources, you can download weights directly instead of using the Gemini API to generate content. Consider Gemma and Code Gemma, an open-source models **available for on-premises use**.
 | Model         | Type              | Access                              | Details                                                                                                           |
 |:---------------:|:-------------------:|:-------------------------------------:|-------------------------------------------------------------------------------------------------------------------|
-| [Gemini](https://huggingface.co/google/gemma-7b)    | 🔐<br>Proprietary       | API only                            | A proprietary multimodal AI by Google DeepMind, Gemini includes advanced models like Gemini Pro and Gemini Pro Vision. Access to Gemini is limited to API use through an [official API](https://aistudio.google.com/) and [unofficial API](https://github.com/dsdanielpark/Gemini-API), and further insights can be gathered from the [paper](https://arxiv.org/abs/2312.11805) and the [official website](https://deepmind.google/technologies/gemini/#introduction) |
-| [Gemma](https://huggingface.co/google/gemma-7b)     | 🤝<br>Open Source       | Downloadable                        | An open-source, text-to-text language model, Gemma is ideal for tasks like question answering and summarization. The model's weights are downloadable for on-premises use, and details are available in the [paper](https://arxiv.org/abs/2403.08295), on the [website](https://ai.google.dev/gemma/docs) |
-| [Code Gemma](https://huggingface.co/google/codegemma-7b-it) | 🤝<br>Open Source       | Downloadable                        | Specifically designed for coding tasks, Code Gemma is another open-source model from Google. It provides downloadable weights to aid developers with code generation and related tasks. More information can be found in the [paper](https://storage.googleapis.com/deepmind-media/gemma/codegemma_report.pdf?utm_source=substack&utm_medium=email), [blog post](https://huggingface.co/blog/codegemma), and the [Hugging Face collection](https://huggingface.co/collections/google/codegemma-release-66152ac7b683e2667abdee11) |
+| [Gemini](https://huggingface.co/google/gemma-7b)    | 🔐<br>Proprietary       | API only<br>[Official API](https://aistudio.google.com), [Unofficial API](https://github.com/dsdanielpark/Gemini-API)                        | A proprietary multimodal AI by Google DeepMind, Gemini includes advanced models like Gemini Pro and Gemini Pro Vision. Access to Gemini is limited to API use, and further insights can be gathered from the [paper](https://arxiv.org/abs/2312.11805) and the [website](https://deepmind.google/technologies/gemini/#introduction) |
+| [Gemma](https://huggingface.co/google/gemma-7b)     | 🤝<br>Open Source       | [Downloadable](https://huggingface.co/google/gemma-7b), [Free API](https://github.com/dsdanielpark/Gemini-API?tab=readme-ov-file#utilize-free-open-source-llm-api-through-open-router)                        | An open-source, text-to-text language model, Gemma is ideal for tasks like question answering and summarization. The model's weights are downloadable for on-premises use, and details are available in the [paper](https://arxiv.org/abs/2403.08295), on the [website](https://ai.google.dev/gemma/docs) |
+| [Code Gemma](https://huggingface.co/google/codegemma-7b-it) | 🤝<br>Open Source       | [Downloadable](https://huggingface.co/google/codegemma-7b-it)                        | Specifically designed for coding tasks, Code Gemma is another open-source model from Google. It provides downloadable weights to aid developers with code generation and related tasks. More information can be found in the [paper](https://storage.googleapis.com/deepmind-media/gemma/codegemma_report.pdf?utm_source=substack&utm_medium=email), [blog post](https://huggingface.co/blog/codegemma), and the [hugging-face collection](https://huggingface.co/collections/google/codegemma-release-66152ac7b683e2667abdee11) |
 
 
 ### Open-source LLM, [Gemma](https://huggingface.co/google/gemma-7b)