Huggingface: Instruction Tuning Seq2Seq Models

[kevinscaria]

Problem Description This notebook demonstrates how to instruction tune SeqSeq models using huggingface transformers. Instruction tuning is a machine learning paradigm where a model is trained to follow instructions for a given task. Instructions facilitate large language models (LLMs) with in-context learning to improve performance.

[FlorentLvr]

Hello @kevinscaria, I am glad you want to contribute on our repository! 🚀 Please follow these instructions to start contributing. -> https://github.com/jupyter-naas/awesome-notebooks/blob/master/README.md#how-to-contribute Let me know if you have any questions! :pray: Cheers!

[kevinscaria]

@FlorentLvr I have completed the same.

[FlorentLvr]

@FlorentLvr I have completed the same.

Great! You should received an email to join our team on GitHub. :rocket: You can now go to step2 for the technical and then start working on your template: https://github.com/jupyter-naas/awesome-notebooks#step-2-technical-setup Let me know if you have any questions :)