(p, proc)
940 continue
941 deserializers[name] = lambda p, proc=proc: proc.from_disk(
--> 942 p, exclude=["vocab"]
943 )
944 if not (path / "vocab").exists() and "vocab" not in exclude:
pipes.pyx in spacy.pipeline.pipes.Pipe.from_disk()
/opt/anaconda3/envs/spacy/lib/python3.7/site-packages/spacy/util.py in from_disk(path, readers, exclude)
652 # Split to support file names like meta.json
653 if key.split(".")[0] not in exclude:
--> 654 reader(path / key)
655 return path
656
pipes.pyx in spacy.pipeline.pipes.Pipe.from_disk.load_model()
pipes.pyx in spacy.pipeline.pipes.TextCategorizer.Model()
/opt/anaconda3/envs/spacy/lib/python3.7/site-packages/spacy/_ml.py in Tok2Vec(width, embed_size, **kwargs)
320 if not USE_MODEL_REGISTRY_TOK2VEC:
321 # Preserve prior tok2vec for backwards compat, in v2.2.2
--> 322 return _legacy_tok2vec.Tok2Vec(width, embed_size, **kwargs)
323 pretrained_vectors = kwargs.get("pretrained_vectors", None)
324 cnn_maxout_pieces = kwargs.get("cnn_maxout_pieces", 3)
/opt/anaconda3/envs/spacy/lib/python3.7/site-packages/spacy/ml/_legacy_tok2vec.py in Tok2Vec(width, embed_size, **kwargs)
42 prefix, suffix, shape = (None, None, None)
43 if pretrained_vectors is not None:
---> 44 glove = StaticVectors(pretrained_vectors, width, column=cols.index(ID))
45
46 if subword_features:
/opt/anaconda3/envs/spacy/lib/python3.7/site-packages/thinc/neural/_classes/static_vectors.py in __init__ (self, lang, nO, drop_factor, column)
41 # same copy of spaCy if they're deserialised.
42 self.lang = lang
---> 43 vectors = self.get_vectors()
44 self.nM = vectors.shape[1]
45 self.drop_factor = drop_factor
/opt/anaconda3/envs/spacy/lib/python3.7/site-packages/thinc/neural/_classes/static_vectors.py in get_vectors(self)
53
54 def get_vectors(self):
---> 55 return get_vectors(self.ops, self.lang)
56
57 def begin_update(self, ids, drop=0.0):
/opt/anaconda3/envs/spacy/lib/python3.7/site-packages/thinc/extra/load_nlp.py in get_vectors(ops, lang)
24 key = (ops.device, lang)
25 if key not in VECTORS:
---> 26 nlp = get_spacy(lang)
27 VECTORS[key] = nlp.vocab.vectors.data
28 return VECTORS[key]
/opt/anaconda3/envs/spacy/lib/python3.7/site-packages/thinc/extra/load_nlp.py in get_spacy(lang, **kwargs)
12
13 if lang not in SPACY_MODELS:
---> 14 SPACY_MODELS[lang] = spacy.load(lang, **kwargs)
15 return SPACY_MODELS[lang]
16
/opt/anaconda3/envs/spacy/lib/python3.7/site-packages/spacy/ __init__.py in load(name, **overrides)
28 if depr_path not in (True, False, None):
29 deprecation_warning(Warnings.W001.format(path=depr_path))
---> 30 return util.load_model(name, **overrides)
31
32
/opt/anaconda3/envs/spacy/lib/python3.7/site-packages/spacy/util.py in load_model(name, **overrides)
167 elif hasattr(name, "exists"): # Path or Path-like to model data
168 return load_model_from_path(name, **overrides)
--> 169 raise IOError(Errors.E050.format(name=name))
170
171
OSError: [E050] Can't find model 'en_vectors_web_lg.vectors'. It doesn't seem to be a shortcut link, a Python package or a valid path to a data directory.
```
spaCy version 2.2.4
Location /opt/anaconda3/envs/spacy/lib/python3.7/site-packages/spacy
Platform Darwin-19.3.0-x86\_64-i386-64bit
Python version 3.7.4
---
### Author:  [@HSM](https://support.prodi.gy/u/HSM)
#### Post date: [March 30, 2020, 2:11pm UTC](https://support.prodi.gy/t/issue-with-exported-spacy-models/999/6 "2020-03-30T14:11:05Z")
@ines, @honnibal. Any idea what goes wrong here?
---
### Author:  [@ines](https://support.prodi.gy/u/ines)
#### Post date: [March 31, 2020, 9:16am UTC](https://support.prodi.gy/t/issue-with-exported-spacy-models/999/7 "2020-03-31T09:16:00Z")
> [@HSM](#):
>
> I got ner and textcat models in my pipeline, which each of them train with different base model and wor2vec vectors
By in your pipeline, do you mean within the same `nlp` object? That's currently not possible – if components were trained with different base models and different vectors, they can't be part of the same `nlp` pipeline, because there can only be one set of vectors that provides the features.
---
### Author:  [@HSM](https://support.prodi.gy/u/HSM)
#### Post date: [March 31, 2020, 12:26pm UTC](https://support.prodi.gy/t/issue-with-exported-spacy-models/999/8 "2020-03-31T12:26:02Z")
@ines Yes, the same nlp.
I can create a custom pipeline by adding all those NER and Textcat models and run the model with no problem. When I create a Python package and load it again, I get those error messages.
I can fix it by changing the meta data, but once I open a new Jupyter notebook, it asks for another vectors name.
---
### Author:  [@ines](https://support.prodi.gy/u/ines)
#### Post date: [April 1, 2020, 9:10am UTC](https://support.prodi.gy/t/issue-with-exported-spacy-models/999/9 "2020-04-01T09:10:57Z")
> [@HSM](#):
>
> I can fix it by changing the meta data, but once I open a new Jupyter notebook, it asks for another vectors name.
It's definitely confusing, but I think you ended up in a weird state here where the vectors in the `meta.json` don't match the vectors in the individual component `cfg` (maybe have a look at that in the model data directories as well) – which makes sense, because they did indeed use different vectors.
So even if you do manage to trick spaCy into thinking it's all the same vectors, you might still see different results for the components trained with different vectors. Maybe it's easiest to start fresh and save out the pipelines separately, or retrain so that all components use the same base model.
---
### Author:  [@Mayank](https://support.prodi.gy/u/Mayank)
#### Post date: [June 2, 2020, 12:57pm UTC](https://support.prodi.gy/t/issue-with-exported-spacy-models/999/10 "2020-06-02T12:57:59Z")
Hi Ines
I've run command line `spacy train` for NER with base model as `nlp = spacy.load("en_core_web_lg")` but it sends me the error like _OSError: [E050] Can't find model 'nlp'. It doesn't seem to be a shortcut link, a Python package or a valid path to a data directory._ Even though the model has been loaded successfully. I'm doing all in Googe colab.
After running `spacy validate` I got this:
My workflow is like that:
base model : en\_core\_web\_lg,
vector: en\_vector\_web\_lg
pretrained: same model you've used in food ingredients
Thanks
---
### Author:  [@ines](https://support.prodi.gy/u/ines)
#### Post date: [June 2, 2020, 2:10pm UTC](https://support.prodi.gy/t/issue-with-exported-spacy-models/999/11 "2020-06-02T14:10:29Z")
> [@Mayank](#):
>
> _OSError: [E050] Can't find model 'nlp'. It doesn't seem to be a shortcut link, a Python package or a valid path to a data directory._
How are you loading the model? The error message mirrors exactly what's passed into the call to `spacy.load()` so it sounds like somewhere in your code, you're calling `spacy.load("nlp")`?
---
### Author:  [@Mayank](https://support.prodi.gy/u/Mayank)
#### Post date: [June 2, 2020, 2:33pm UTC](https://support.prodi.gy/t/issue-with-exported-spacy-models/999/12 "2020-06-02T14:33:27Z")
I am calling as `spacy.load("en_vectors_web_lg")`. It works in google colab. But when I run the same code into my local terminal or jupyter notebook it throws me the following error:
Also, I have run this `spacy validate`
Please help
Thanks
---
### Author:  [@salhasalman](https://support.prodi.gy/u/salhasalman)
#### Post date: [May 21, 2021, 9:14am UTC](https://support.prodi.gy/t/issue-with-exported-spacy-models/999/13 "2021-05-21T09:14:07Z")
@Mayank did u find a solution for this
---
### Author:  [@SofieVL](https://support.prodi.gy/u/SofieVL)
#### Post date: [May 21, 2021, 4:45pm UTC](https://support.prodi.gy/t/issue-with-exported-spacy-models/999/14 "2021-05-21T16:45:40Z")
Hi @salhasalman.
This thread is already a bit old and possibly outdated.
If you're running into spacy-specific issues with loading models, we'll be able to help you better if you open a discussion thread at [Discussions · explosion/spaCy · GitHub](https://github.com/explosion/spaCy/discussions), and provide a minimal code snippet that reproduces the error and/or paste the full error stack trace.