Abneet Wats

Process multi line to convert it into string following code might help: `fo = open("file.txt", "r")` `text = (fo.read())..encode("ascii", errors="ignore").decode()` `p = Parser()` `p.load_models("/path to model/")` `p.predict(text)`

Also You can chgange load method in ner.py as def load_models(self, loc=None): if not loc: loc = os.path.join(os.path.expanduser('~'), '.ner_model') self.model = load_model(os.path.join(loc,"model.h5")) # loading word2Idx np.load.__defaults__=(None, True, True, 'ASCII') self.word2Idx...

Please delete dangling objects by ```bash gdrive delete 0ByqE7lC_kho3SXFmTHF6TkxDajA gdrive sync upload /home/backupdb/ 0ByqE7lC_kho3ZHVCb3hCMXNRQXM ``` You can write bash script to first check all dangling objects then run delete then...

add -e for example ```cmd python.exe $script -v -k items $folder$i.json > $folder$i.csv -e utf-8 ``` you can replace utf-8 with your encoding as utf-16 or utf-32 or utf-8-sig(if error...

if you are using windows try with encoding 'latin1', 'iso-8859-1' or 'cp1252' also, if that doesn't work, set following environment variable ```cmd set PYTHONIOENCODING=windows-1252 set PYTHONLEGACYWINDOWSSTDIO=windows-1252 ```