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Fix link to the finetuning notebook in doc #743

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Oct 18, 2024
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4 changes: 2 additions & 2 deletions doc/faq.md
Original file line number Diff line number Diff line change
Expand Up @@ -146,13 +146,13 @@ NOTE: It is important to choose the correct model type when you opt for the abov

### 1. I have a microscopy dataset I would like to fine-tune Segment Anything for. Is it possible using `micro_sam`?
Yes, you can fine-tune Segment Anything on your own dataset. Here's how you can do it:
- Check out the [tutorial notebook](https://github.com/computational-cell-analytics/micro-sam/blob/master/notebooks/micro-sam-finetuning.ipynb) on how to fine-tune Segment Anything with our `micro_sam.training` library.
- Check out the [tutorial notebook](https://github.com/computational-cell-analytics/micro-sam/blob/master/notebooks/sam_finetuning.ipynb) on how to fine-tune Segment Anything with our `micro_sam.training` library.
- Or check the [examples](https://github.com/computational-cell-analytics/micro-sam/tree/master/examples/finetuning) for additional scripts that demonstrate finetuning.
- If you are not familiar with coding in python at all then you can also use the [graphical interface for finetuning](finetuning-ui). But we recommend using a script for more flexibility and reproducibility.


### 2. I would like to fine-tune Segment Anything on open-source cloud services (e.g. Kaggle Notebooks), is it possible?
Yes, you can fine-tune Segment Anything on your custom datasets on Kaggle (and [BAND](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html#using-micro_sam-on-band)). Check out our [tutorial notebook](https://github.com/computational-cell-analytics/micro-sam/blob/master/notebooks/micro-sam-finetuning.ipynb) for this.
Yes, you can fine-tune Segment Anything on your custom datasets on Kaggle (and [BAND](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html#using-micro_sam-on-band)). Check out our [tutorial notebook](https://github.com/computational-cell-analytics/micro-sam/blob/master/notebooks/sam_finetuning.ipynb) for this.


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