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Community tutorials are made by active members of the Hugging Face community that want to share their knowledge and expertise with others. They are a great way to learn about the library and its features, and to get started with core classes and modalities.
| 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)|
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| 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)|
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| 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)|
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| 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)|
| 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)|
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| 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)|
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## Contributing
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If you have a tutorial that you would like to add to this list, please open a PR to add it. We will review it and merge it if it is relevant to the community.
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