diff --git a/docs/source/community_tutorials.md b/docs/source/community_tutorials.md
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--- a/docs/source/community_tutorials.md
+++ b/docs/source/community_tutorials.md
@@ -4,19 +4,19 @@ Community tutorials are made by active members of the Hugging Face community tha
 
 # Language Models
 
-| Task                    | Class           | Description                                                                              | Author                                                         | Tutorial                                                                                                             |
-| ----------------------- | --------------- | ---------------------------------------------------------------------------------------- | -------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------- |
-| Instruction tuning      | [`SFTTrainer`]  | Fine-tuning Google Gemma LLMs using ChatML format with QLoRA                             | [Philipp Schmid](https://huggingface.co/philschmid)            | [Link](https://www.philschmid.de/fine-tune-google-gemma)                                                             |
-| Structured Generation   | [`SFTTrainer`]  | Fine-tuning Llama-2-7B to generate Persian product catalogs in JSON using QLoRA and PEFT | [Mohammadreza Esmaeilian](https://huggingface.co/Mohammadreza) | [Link](https://huggingface.co/learn/cookbook/en/fine_tuning_llm_to_generate_persian_product_catalogs_in_json_format) |
-| Preference Optimization | [`DPOTrainer`]  | Align Mistral-7b using Direct Preference Optimization for human preference alignment     | [Maxime Labonne](https://huggingface.co/mlabonne)              | [Link](https://mlabonne.github.io/blog/posts/Fine_tune_Mistral_7b_with_DPO.html)                                     |
-| Preference Optimization | [`ORPOTrainer`] | Fine-tuning Llama 3 with ORPO combining instruction tuning and preference alignment      | [Maxime Labonne](https://huggingface.co/mlabonne)              | [Link](https://mlabonne.github.io/blog/posts/2024-04-19_Fine_tune_Llama_3_with_ORPO.html)                            |
+| Task                    | Class           | Description                                                                              | Author                                                         | Tutorial                                                                                                             | Colab                                                                                                                                                                                                                                        |
+| ----------------------- | --------------- | ---------------------------------------------------------------------------------------- | -------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| Instruction tuning      | [`SFTTrainer`]  | Fine-tuning Google Gemma LLMs using ChatML format with QLoRA                             | [Philipp Schmid](https://huggingface.co/philschmid)            | [Link](https://www.philschmid.de/fine-tune-google-gemma)                                                             | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/philschmid/deep-learning-pytorch-huggingface/blob/main/training/gemma-lora-example.ipynb)                              |
+| Structured Generation   | [`SFTTrainer`]  | Fine-tuning Llama-2-7B to generate Persian product catalogs in JSON using QLoRA and PEFT | [Mohammadreza Esmaeilian](https://huggingface.co/Mohammadreza) | [Link](https://huggingface.co/learn/cookbook/en/fine_tuning_llm_to_generate_persian_product_catalogs_in_json_format) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/cookbook/blob/main/notebooks/en/fine_tuning_llm_to_generate_persian_product_catalogs_in_json_format.ipynb) |
+| Preference Optimization | [`DPOTrainer`]  | Align Mistral-7b using Direct Preference Optimization for human preference alignment     | [Maxime Labonne](https://huggingface.co/mlabonne)              | [Link](https://mlabonne.github.io/blog/posts/Fine_tune_Mistral_7b_with_DPO.html)                                     | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mlabonne/llm-course/blob/main/Fine_tune_a_Mistral_7b_model_with_DPO.ipynb)                                             |
+| Preference Optimization | [`ORPOTrainer`] | Fine-tuning Llama 3 with ORPO combining instruction tuning and preference alignment      | [Maxime Labonne](https://huggingface.co/mlabonne)              | [Link](https://mlabonne.github.io/blog/posts/2024-04-19_Fine_tune_Llama_3_with_ORPO.html)                            | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1eHNWg9gnaXErdAa8_mcvjMupbSS6rDvi)                                                                                      |
 
 # Vision Language Models
 
-| Task            | Class          | Description                                                                  | Author                                                 | Tutorial                                                             |
-| --------------- | -------------- | ---------------------------------------------------------------------------- | ------------------------------------------------------ | -------------------------------------------------------------------- |
-| Visual QA       | [`SFTTrainer`] | Fine-tuning Qwen2-VL-7B for visual question answering on ChartQA dataset     | [Sergio Paniego](https://huggingface.co/sergiopaniego) | [Link](https://huggingface.co/learn/cookbook/fine_tuning_vlm_trl)    |
-| SEO Description | [`SFTTrainer`] | Fine-tuning Qwen2-VL-7B for generating SEO-friendly descriptions from images | [Philipp Schmid](https://huggingface.co/philschmid)    | [Link](https://www.philschmid.de/fine-tune-multimodal-llms-with-trl) |
+| Task            | Class          | Description                                                                  | Author                                                 | Tutorial                                                             | Colab                                                                                                                                                                                                                           |
+| --------------- | -------------- | ---------------------------------------------------------------------------- | ------------------------------------------------------ | -------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| Visual QA       | [`SFTTrainer`] | Fine-tuning Qwen2-VL-7B for visual question answering on ChartQA dataset     | [Sergio Paniego](https://huggingface.co/sergiopaniego) | [Link](https://huggingface.co/learn/cookbook/fine_tuning_vlm_trl)    | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/cookbook/blob/main/notebooks/en/fine_tuning_vlm_trl.ipynb)                                    |
+| SEO Description | [`SFTTrainer`] | Fine-tuning Qwen2-VL-7B for generating SEO-friendly descriptions from images | [Philipp Schmid](https://huggingface.co/philschmid)    | [Link](https://www.philschmid.de/fine-tune-multimodal-llms-with-trl) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/philschmid/deep-learning-pytorch-huggingface/blob/main/training/fine-tune-multimodal-llms-with-trl.ipynb) |
 
 ## Contributing