Alex Strick van Linschoten
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add accuracy comment
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I've been working through the first two lessons of [the fastai course](https://course.fast.ai/). For lesson one I trained a model to recognise my cat, Mr Blupus. For lesson two the emphasis is on getting those models out in the world as some kind of demo or application. [Gradio](https://gradio.app) and [Huggingface Spaces](https://huggingface.co/spaces) makes it super easy to get a prototype of your model on the internet.
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## The Dataset
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I downloaded a few thousand publicly-available FOIA documents from a government website. I split the PDFs up into individual `.jpg` files and then used [Prodigy](https://prodi.gy/) to annotate the data. (This process was described in [a blogpost written last year](https://mlops.systems/fastai/redactionmodel/computervision/datalabelling/2021/09/06/redaction-classification-chapter-2.html).)
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I've been working through the first two lessons of [the fastai course](https://course.fast.ai/). For lesson one I trained a model to recognise my cat, Mr Blupus. For lesson two the emphasis is on getting those models out in the world as some kind of demo or application. [Gradio](https://gradio.app) and [Huggingface Spaces](https://huggingface.co/spaces) makes it super easy to get a prototype of your model on the internet.
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This model has an accuracy of ~96% on the validation dataset.
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## The Dataset
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I downloaded a few thousand publicly-available FOIA documents from a government website. I split the PDFs up into individual `.jpg` files and then used [Prodigy](https://prodi.gy/) to annotate the data. (This process was described in [a blogpost written last year](https://mlops.systems/fastai/redactionmodel/computervision/datalabelling/2021/09/06/redaction-classification-chapter-2.html).)
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