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prepare for LFS

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  1. .gitattributes +3 -0
  2. README.md +23 -1
.gitattributes CHANGED
@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ l1-model/* filter=lfs diff=lfs merge=lfs -text
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+ l2-models/* filter=lfs diff=lfs merge=lfs -text
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README.md CHANGED
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  - programming
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  - computer-science
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  - learning
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - programming
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  - computer-science
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  - learning
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+ ---
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+ # AISOP-oop-classifiers
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+ This is a series of spacy models for the classification tasks.
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+ ## Try it here
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+ - Install spaCy
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+ - `python python recognize.py l1-model l2-models "this is a text"`
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+ ...outputs the recognition in JSON.
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+ ## Web-App Packaging
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+ This model is part of the AISOP-domain-fundid https://gitlab.com/aisop/aisop-domain-oop which is designed to serve for the [AISOP-webapp](https://gitlab.com/aisop/aisop-webapp).
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+ The [python scripts](https://gitlab.com/aisop/aisop-webapp/-/tree/main/scripts/python?ref_type=heads) there use the models and the spaCy library to classify each "paragraph" of e-portfolios stored in HTML and even generate words using tesseract (if the picture is available) and annotate them too.
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+ The scripts enrich the HTML with `data-topic-*` attributes, indicating the presence of topics in the paragraphs.
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+ The scripts can be tested in the web-app in the `/debug/` road.