# Cannot run prodigy ner.teach after update **URL:** \ **Category:** Uncategorized\ **Tags:** install, spacy\ **Created:** [October 9, 2017, 4:29pm UTC](https://support.prodi.gy/t/cannot-run-prodigy-ner-teach-after-update/52 "2017-10-09T16:29:53Z")\ **Posts on this page:** 2\ **Page:** 1
**Author:** ![Mede](https://avatars.discourse-cdn.com/v4/letter/m/a3d4f5/32.png) [@Mede](https://support.prodi.gy/u/Mede)\ **Post date:** [October 9, 2017, 4:29pm UTC](https://support.prodi.gy/t/cannot-run-prodigy-ner-teach-after-update/52/1 "2017-10-09T16:29:53Z")
Hi, After installing the update you sent out four days ago I am unable to run prodigy, despite using the exact command on the exact same dataset and training data that was working before the update. I get the following error messages: $ prodigy ner.teach engelsk\_model en\_core\_web\_sm traindata.txt --label ORG Traceback (most recent call last): File “/usr/lib/python3.5/runpy.py”, line 184, in \_run\_module\_as\_main “ **main** ”, mod\_spec) File “/usr/lib/python3.5/runpy.py”, line 85, in \_run\_code exec(code, run\_globals) File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/prodigy/ **main**.py”, line 235, in controller = recipe(_args, use\_plac=True) File “cython\_src/prodigy/core.pyx”, line 129, in prodigy.core.recipe.recipe\_decorator.recipe\_proxy File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/plac\_core.py”, line 328, in call cmd, result = parser.consume(arglist) File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/plac\_core.py”, line 207, in consume return cmd, self.func(_(args + varargs + extraopts), \*\*kwargs) File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/prodigy/recipes/ner.py”, line 53, in teach model = EntityRecognizer(spacy.load(spacy\_model), label=label) File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/spacy/ **init**.py”, line 15, in load return util.load\_model(name, \*\*overrides) File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/spacy/util.py”, line 104, in load\_model return load\_model\_from\_link(name, \*\*overrides) File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/spacy/util.py”, line 123, in load\_model\_from\_link return cls.load(\*\*overrides) File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/spacy/data/en\_core\_web\_sm/ **init**.py”, line 12, in load return load\_model\_from\_init\_py( **file** , \*\*overrides) File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/spacy/util.py”, line 156, in load\_model\_from\_init\_py return load\_model\_from\_path(data\_path, meta, \*\*overrides) File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/spacy/util.py”, line 139, in load\_model\_from\_path return nlp.from\_disk(model\_path) File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/spacy/language.py”, line 540, in from\_disk util.from\_disk(path, deserializers, exclude) File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/spacy/util.py”, line 486, in from\_disk reader(path / key) File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/spacy/language.py”, line 536, in deserializers[proc.name] = lambda p, proc=proc: proc.from\_disk(p, vocab=False) File “pipeline.pyx”, line 205, in spacy.pipeline.BaseThincComponent.from\_disk File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/spacy/util.py”, line 486, in from\_disk reader(path / key) File “pipeline.pyx”, line 198, in spacy.pipeline.BaseThincComponent.from\_disk.load\_model File “/home/mede/Desktop/\_OVERFOERES/CluedIn/NER\_extraction/spacyNER/prodigy\_installation/virtualenv\_prodigy/lib/python3.5/site-packages/thinc/neural/\_classes/model.py”, line 351, in from\_bytes dest = getattr(layer, name) AttributeError: ‘FeedForward’ object has no attribute ‘G’ I have no idea what this means or how to fix it. Any help you might be able to provide would be greatly appreciated. ---
**Author:** ![honnibal](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/honnibal/32/35_2.png) [@honnibal](https://support.prodi.gy/u/honnibal)\ **Post date:** [October 9, 2017, 4:54pm UTC](https://support.prodi.gy/t/cannot-run-prodigy-ner-teach-after-update/52/2 "2017-10-09T16:54:57Z")
Hi, We haven’t found a way to make that error nicer yet, so sorry it’s so cryptic. You probably need to run: ```python spacy download en_core_web_sm --force ``` This sort of error means that the weights being read from disk don’t match the architecture defined in the code. My guess is that the mode being loaded is one of our pre-trained ones. The command above would redownload it, and force the overwrite. If you’re trying to load a model you previously trained yourself, you’ll have to retrain it. Regrettably the same situation is likely to occur again on the next version. The models for spaCy 2 are improving very quickly, and we’re trying to find the best balance of speed and accuracy. The good news is that results are really good — and we’re getting very close to the spaCy 2 release candidate, after which things will be more stable.