diff --git a/README.md b/README.md
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--- a/README.md
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 # tessdata_contrib
 
-User contributed (non Google) data repository for Tesseract 4 and 5 (Akkadian, Ancient Greek, Old Persian languages, ...)
+User contributed (non Google) data repository for Tesseract 4 and 5 (Akkadian, Ancient Greek, Old Persian languages, Hebrew Rashi Script ...)
diff --git a/heb_rashi/TRAINING.md b/heb_rashi/TRAINING.md
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+
+
+# Creating Tesseract training data
+
+The instructions bellow were tested on Linux Debian 11.
+
+```
+sudo apt update
+sudo apt install tesseract-ocr libtesseract-dev unzip tmux openmpi-bin
+mkdir -p ~/tessdata_heb_rashi/langdata/heb
+```
+
+
+## Word list
+
+Generate Torah literature related [word list](tesseract_4.1.1/langdata/heb/heb.wordlist) from [Sefaria's MongoDB dump](https://storage.googleapis.com/sefaria-mongo-backup/dump_small.tar.gz) with words ordered by decreasing frequency.
+
+```
+# Download the dump, decompress and import it:
+
+wget https://storage.googleapis.com/sefaria-mongo-backup/dump_small.tar.gz
+tar -xzf dump_small.tar.gz
+mongorestore dump
+
+
+# Convert ' (i.e. \x{27}) and \" to geresh/gershayim and replace each non-Hebrew letter group with a newline, etc.:
+
+mongo sefaria --eval "db.getCollection('texts').find({'language': 'he'}).forEach(function(f){print(tojson(f, '', true));})" | perl -Mutf8 -CS -pE 's/\x{27}/׳/g;s/\\"/״/g;s/\P{Hebrew}+/\n/g;s/^״+$//gm' > texts_hebrew_only.txt
+
+
+# Sort while counting and eliminating duplicates/entries with occurrence less than 16:
+
+sort --buffer-size=1G texts_hebrew_only.txt | uniq -c | sort -gr | awk '{if ($1 > 15)  print $2}' > heb.wordlist
+```
+
+Afterwards delete several empty lines at the beginning and the end of the `langdata/heb/heb.wordlist` file manually.
+
+
+## Fonts
+
+[Rashi fonts](https://drive.google.com/file/d/1Um3yGV7dT_6AEs7DQU_oC5GpHwZlzR9N/view?usp=sharing) used to render synthetic training data images are listed inside the [tesseract_4.1.1/langdata/heb/okfonts.txt](tesseract_4.1.1/langdata/heb/okfonts.txt). All fonts from `FontsRashi/Working` worked well for the training:
+
+```
+text2image --list_available_fonts --fonts_dir FontsRashi/Working
+  0: BenOr Rashi
+  1: Guttman Rashi
+  2: Guttman Rashi Bold
+  3: Mekorot-Rashi Bold
+  4: Mekorot-Rashi Medium
+  5: Mekorot-Rashi Medium Italic
+  6: PFT_Rashi
+  7: PFT_Rashi Light
+  8: RashiAmiti
+  9: Rashy
+ 10: ZWXLDX+RasheeMF-Medium Medium
+```
+
+
+If you have an idea how to fix the fonts from `FontsRashi/NonWorking` (maybe using [FontForge](https://fontforge.org/) or similar) - please [report](https://gitlab.com/pninim.org/tessdata_heb_rashi/-/issues)!
+
+
+
+## Determine xheights for Rashi fonts
+
+File [tesseract_4.1.1/langdata/Hebrew.xheights](tesseract_4.1.1/langdata/Hebrew.xheights) was enhanced by Rashi fonts using `grctraining` as follows:
+
+```
+git clone https://ancientgreekocr.org/grctraining.git
+cd grctraining
+make tools/xheight
+cd tools/
+./xheight 'Mekorot-Rashi Medium'
+... and so on for all fonts listed in okfonts.txt
+```
+
+
+## Download remaining necessary files
+
+```
+cd ~/tessdata_heb_rashi/langdata
+
+wget https://raw.githubusercontent.com/tesseract-ocr/langdata_lstm/master/Hebrew.unicharset
+wget https://raw.githubusercontent.com/tesseract-ocr/langdata_lstm/master/Latin.unicharset
+wget https://raw.githubusercontent.com/tesseract-ocr/langdata_lstm/master/Latin.xheights
+wget https://raw.githubusercontent.com/tesseract-ocr/langdata_lstm/master/radical-stroke.txt
+wget https://raw.githubusercontent.com/tesseract-ocr/langdata_lstm/master/font_properties
+
+cd heb
+
+wget https://raw.githubusercontent.com/tesseract-ocr/langdata_lstm/master/heb/desired_characters
+wget https://raw.githubusercontent.com/tesseract-ocr/langdata_lstm/master/heb/forbidden_characters
+wget https://raw.githubusercontent.com/tesseract-ocr/langdata_lstm/master/heb/heb.numbers
+wget https://raw.githubusercontent.com/tesseract-ocr/langdata_lstm/master/heb/heb.punc
+wget https://raw.githubusercontent.com/tesseract-ocr/langdata_lstm/master/heb/heb.singles_text
+wget https://raw.githubusercontent.com/tesseract-ocr/langdata_lstm/master/heb/heb.unicharambigs
+wget https://raw.githubusercontent.com/tesseract-ocr/langdata_lstm/master/heb/heb.unicharset
+```
+
+
+## ScrollView
+
+**Optional step:** download and build ScrollView to visualize the training process. Not needed if `lstmtraining --debug_interval -1` (shows text information on every iteration) or `lstmtraining --debug_interval 0` (shows text information on every 100 iterations) are used.
+
+```
+# Create ScrollView (optional)
+
+apt install openjdk-11-jdk
+git clone https://github.com/tesseract-ocr/tesseract
+cd tesseract
+./autogen.sh
+./configure
+cd java
+make ScrollView.jar
+
+Now run `lstmtraining` from here to utilize ScrollView.jar
+```
+
+## Generate training corpus
+
+```
+cd /usr/share/tesseract-ocr
+sudo rm language-specific.sh tesstrain.sh tesstrain_utils.sh
+sudo wget https://raw.githubusercontent.com/tesseract-ocr/tesseract/4.0/src/training/language-specific.sh
+sudo wget https://raw.githubusercontent.com/tesseract-ocr/tesseract/4.0/src/training/tesstrain.sh
+sudo wget https://raw.githubusercontent.com/tesseract-ocr/tesseract/4.0/src/training/tesstrain_utils.sh
+sudo chmod a+x *sh
+```
+
+
+
+### Create training data
+
+Use all but one font:
+
+```
+mkdir -p ~/tessdata_heb_rashi/output/train
+/usr/share/tesseract-ocr/tesstrain.sh --fonts_dir FontsRashi/Working --lang heb --linedata_only --noextract_font_properties --langdata_dir ./langdata  --tessdata_dir /usr/share/tesseract-ocr/4.00/tessdata/ --output_dir output/train --fontlist 'BenOr Rashi' 'Guttman Rashi Bold' 'Mekorot-Rashi Bold' 'Mekorot-Rashi Medium' 'Mekorot-Rashi Medium Italic' 'PFT_Rashi' 'PFT_Rashi Light' 'RashiAmiti' 'Rashy' 'ZWXLDX+RasheeMF-Medium Medium'
+```
+
+Since the above command may take a lot of time - it is recommended to run it inside [tmux](https://github.com/tmux/tmux). Furthermore it might be beneficial to run the command for each font separately in a separate `tmux` session, e.g.: `/usr/share/tesseract-ocr/tesstrain.sh --fonts_dir FontsRashi/Working --lang heb --linedata_only --noextract_font_properties --langdata_dir ./langdata  --tessdata_dir /usr/share/tesseract-ocr/4.00/tessdata/ --output_dir output/train --fontlist 'BenOr Rashi'` and so on.
+
+### Create evaluation data 
+
+Use the remaining font for evaluation:
+
+```
+mkdir -p ~/tessdata_heb_rashi/output/evaluate
+/usr/share/tesseract-ocr/tesstrain.sh --fonts_dir FontsRashi/Working --lang heb --linedata_only --noextract_font_properties --langdata_dir ./langdata  --tessdata_dir /usr/share/tesseract-ocr/4.00/tessdata/ --output_dir output/evaluate --fontlist 'Guttman Rashi'
+```
+
+### Train
+
+check the number at the top of `output/train/heb/heb.unicharset` - 72 and use it in the command line bellow (O1c72):
+
+```
+OMP_THREAD_LIMIT=11 lstmtraining --debug_interval 0 \
+  --traineddata ~/tessdata_heb_rashi/output/train/heb/heb.traineddata \
+  --net_spec '[1,36,0,1 Ct3,3,16 Mp3,3 Lfys48 Lfx96 Lrx96 Lfx256 O1c72]' \
+  --model_output ~/tessdata_heb_rashi/output/base --learning_rate 20e-4 \
+  --train_listfile ~/tessdata_heb_rashi/output/train/heb.training_files.txt \
+  --eval_listfile ~/tessdata_heb_rashi/output/evaluate/heb.training_files.txt \
+  --max_iterations 50000 &>~/tessdata_heb_rashi/output/basetrain.log
+```
+
+
+# Test results
+```
+lstmeval --model ~/tessdata_heb_rashi/output/base_checkpoint \
+  --traineddata ~/tessdata_heb_rashi/output/train/heb/heb.traineddata \
+  --eval_listfile ~/tessdata_heb_rashi/output/evaluate/heb.training_files.txt
+```
+
+# Convert checkpoint to best (float) traindata
+```
+lstmtraining --stop_training --continue_from output/base_checkpoint --traineddata ~/tessdata_heb_rashi/output/train/heb/heb.traineddata --model_output ~/tessdata_heb_rashi/output/heb_rashi.traineddata
+```
+
+# Convert checkpoint to fast (integer) traindata
+```
+lstmtraining --stop_training --convert_to_int --continue_from output/base_checkpoint --traineddata ~/tessdata_heb_rashi/output/train/heb/heb.traineddata --model_output ~/tessdata_heb_rashi/output/heb_rashi.fast.traineddata
+```
+
diff --git a/heb_rashi/best/heb_rashi.traineddata b/heb_rashi/best/heb_rashi.traineddata
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diff --git a/heb_rashi/fast/heb_rashi.traineddata b/heb_rashi/fast/heb_rashi.traineddata
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