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Hi, thanks for sharing the great work. I would love to adapt your mechanism into my project. However, I have some questions that I hope you can help address.
- You mentioned "For robust training, include the new data in a large data mix (e.g., our provided SFT blend)." in the fine-tuning example. I am unsure what is the large data mix over here? Do you mean we have to add my training data with your pretrain data? However, isn't your data private?
- How much data should be sufficient (number of samples) for the domain specific fine-tuning phase?
- I have a small specific dataset with text labels (which can be used for the fine-tuning) but I also have a much bigger medical image data source (w/o labels). Do you think we could leverage the the big data source (w/o labels) somewhere in your pipeline to make the model more power?
Thank you!
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