LLAMA-2: Fine-tune Models Easily with Auto Train

:computer: You can fine-tune a Llama-2 model on your own dataset using a single line of code.

:package: To run this locally, you need to download the Auto Train Advance package from Hugging Face's GitHub repo.

:rocket: An Nvidia GPU is required for model fine-tuning, but you can use Google Colab if you don't have one.

🦙 The video explains how to fine-tune models using the Auto Train package from Hugging Face.

🙌 The code provided demonstrates how to specify the project name and the model to be fine-tuned.

📝 It is important to note that this method can be used with any model from Hugging Face, not just the llama models.

🦙 You can create a sharded version of the original gamma model site using any available version.

🙌 To fine-tune the model, you need to provide the name or path to the dataset.

📁 You can upload your data to hugging face or provide the local path to the dataset.

🦙 The video discusses the formatting of the data set for the LLAMA-2 model.

🙌 It emphasizes the importance of using special tokens in the data set for the model to understand the input and output.

👥 The format of the data set for fine-tuning the base model is different from the prompt template used in Lemma 2 chat models.

🦙 Using the 'use' command, the model can be fine-tuned on custom data.

🙌 The learning rate controls the speed of conversion during the training process.

🔧 The trainer used is 'sft', which stands for supervised fine-tuning.

🦙 Fine-tuning a large language model using your own training data set takes time, but it can be done using a single NF code.

🙌 During the training process, a project folder is created to track the progress, and once complete, you can find the config.json file, tokenizer, and model file in the folder.

📊 To push the fine-tuned model to your own account, you need to provide the repo ID and be patient as it may take at least an hour to appear.

🦙 Learn how to fine-tune a large language model on your own data set using the Auto Train package.

🔍 Discover the process of creating your own data sets instead of using pre-existing ones on Hugging Face.

💻 Ensure you have a powerful GPU to effectively run the fine-tuning process.