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Finetuning Granite Speech #307
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Check out this pull request on See visual diffs & provide feedback on Jupyter Notebooks. Powered by ReviewNB |
Hi, thanks for your contribution! The cookbook recipes are more focused on applied use cases so it'd be awesome if you could tailor it more towards solving a specific problem or use case. |
Might not really be my place to say, but even though this script perhaps doesn't focus on tackling a specific fine-tuning use-case (i.e. domain specific fine-tuning on medical audio etc.), it is nevertheless very important to provide the open-source community with a script to fine-tune a new open-source model on their custom data. Maybe this is in the works already and I'm just jumping the gun, but this contribution surely should exist somewhere within the cookbook or some other resource until perhaps a better, and more robust implementation is available. Just my thoughts. |
Absolutely, we're happy to have a link for it in the Granite Speech docs in Transformers if nothing else! |
Hi @stevhliu, thanks for the feedback! We can also finetune Granite Speech on an unseen task like spoken question answering, but I fear people won't find it as useful (a finetuning script was requested here and here ). I hope it will be suitable for the cookbook - I like the fact that the huggingface webpage presents the notebook nicely. 🙏 |
I'm wondering if there is some way we can apply your fine-tuning recipe to a more practical application. For example, you can fine-tune Granite Speech and build a Space that transcribes meeting notes, captions videos, etc. This will help you extend the notebook and demonstrate how you can build an AI application with it. If you decide to keep it as fine-tuning only, then I think it's best to add it to the Granite Speech docs. Thanks again and we really appreciate the time and effort you put into creating this notebook! 🤗 |
Thanks, @stevhliu. |
Yeah, you can open a PR on the Transformers repo and create a |
What does this PR do?
This PR adds a notebook that shows how to finetune Granite Speech, an open-source model that leads the OpenASR leaderboard.
Who can review?
@merveenoyan @stevhliu can you give that a look? 🙏