Can't find model 'fr_core_news_sm'

[JJMeric]

Hello ! just starting to explore spacy-leff : I have been trying to run the examples given here and on spacy.io
but I stumble on the same error. See below.
I assume it's a simple one, but I did not find help for this in the available documentation (I may not be good at looking at the right place though...).

I intend to use specy-leff, to replace MElt perl utilities, for our bamanan-french parallel corpus. Bamanan or bambara is a language spoken in west africa. See http://cormand.huma-num.fr/

Thanks for help with this...
Jean-Jacques

python3 testleff2.py
Traceback (most recent call last):
File "testleff2.py", line 9, in
nlp = spacy.load('fr_core_news_sm')
File "/usr/local/lib/python3.8/dist-packages/spacy/init.py", line 47, in load
return util.load_model(name, disable=disable, exclude=exclude, config=config)
File "/usr/local/lib/python3.8/dist-packages/spacy/util.py", line 329, in load_model
raise IOError(Errors.E050.format(name=name))
OSError: [E050] Can't find model 'fr_core_news_sm'. It doesn't seem to be a Python package or a valid path to a data directory.

[JJMeric]

OK, I found out by searching for this name "fr_core_news_sm" here on GIThub :
I need to complete the pip install spacy-lefff with this command:
python3 -m spacy download fr_core_news_sm

now it's working ok

[JJMeric]

Still, I am not 100% happy

1. with the example sentence in French :
   Apple cherche a acheter une startup anglaise pour 1 milliard de dollard
   this sentence contains two errors, so I correct it as :
   Apple cherche à acheter une startup anglaise pour 1 milliard de dollars

2. the results
   "cherche" is identified as a noun!? Quite wrong: it is the verb "chercher" in the present tense.
   If I replace it with "cherchait" (past tense), it is identified correctly.

[JJMeric]

trying to use the other example given = trying to use the melt_tagger, I have the following error, please advise:

python3 testleff3.py
Traceback (most recent call last):
File "testleff3.py", line 14, in
nlp.add_pipe('melt_tagger', after='parser')
File "/usr/local/lib/python3.8/dist-packages/spacy/language.py", line 768, in add_pipe
pipe_component = self.create_pipe(
File "/usr/local/lib/python3.8/dist-packages/spacy/language.py", line 659, in create_pipe
resolved = registry.resolve(cfg, validate=validate)
File "/usr/local/lib/python3.8/dist-packages/thinc/config.py", line 727, in resolve
resolved, _ = cls._make(
File "/usr/local/lib/python3.8/dist-packages/thinc/config.py", line 776, in _make
filled, _, resolved = cls._fill(
File "/usr/local/lib/python3.8/dist-packages/thinc/config.py", line 848, in _fill
getter_result = getter(*args, **kwargs)
File "testleff3.py", line 11, in create_melt_tagger
return POSTagger()
File "/usr/local/lib/python3.8/dist-packages/spacy_lefff/melt_tagger.py", line 102, in init
super(
File "/usr/local/lib/python3.8/dist-packages/spacy_lefff/downloader.py", line 20, in init
os.mkdir(os.path.join(download_dir, pkg))
PermissionError: [Errno 13] Permission denied: '/usr/local/lib/python3.8/dist-packages/spacy_lefff/data/tagger'

[JJMeric]

I had t use chown on /usr/local/lib/python3.8/dist-packages/spacy_lefff/data
but that's not making installation easy (we potentially have several platforms).

[sammous]

hello,
Regarding your first point, you have to install spacy french corpus if you wish to use it.
Also i think you are confusing what spaCy POS and Melt Tag is returning, you can refer to this example:

import spacy
from spacy_lefff import LefffLemmatizer, POSTagger
from spacy.language import Language

@Language.factory('french_lemmatizer')
def create_french_lemmatizer(nlp, name):
    return LefffLemmatizer(after_melt=True, default=True)

@Language.factory('melt_tagger')  
def create_melt_tagger(nlp, name):
    return POSTagger()
 
nlp = spacy.load('fr_core_news_sm')
nlp.add_pipe('melt_tagger', after='parser')
nlp.add_pipe('french_lemmatizer', after='melt_tagger')
doc = nlp(u"Apple cherche a acheter une startup anglaise pour 1 milliard de dollard")
for d in doc:
    print(d.text, d.pos_, d._.melt_tagger, d._.lefff_lemma, d.tag_, d.lemma_)

Regarding your permission error, it is because you should use a virtual environment and not your default python since the package downloads the model and writes to a system folder, which you can't access.
You should use virtualenv or any or python virtual environment. (you can refer to this steps )

[ezynsegnane]

In case you use french follow these steps :
setp 1 :
python -m spacy download fr
step 2 :
spacy.load('fr_core_news_sm')

#####################################
In case you use english follow these steps :

setp 1 :
python -m spacy download en
step 2 :
spacy.load('en_core_news_sm')

this comment is for people who will have the same error in the future!