Traceback (most recent call last):


 "cross-wiki.py", line 18, in <module>

cross_encoder = CrossEncoder('cross-encoder/ms-marco-TinyBERT-L-6')


 "/home/zhutian/.conda/envs/infospace/lib/python3.6/site-packages/sentence_transformers/cross_encoder/CrossEncoder.py", line 36, in __init__

self.config = AutoConfig.from_pretrained(model_name)


 "/home/zhutian/.conda/envs/infospace/lib/python3.6/site-packages/transformers/configuration_auto.py", line 272, in from_pretrained

config_dict, _ = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)


 "/home/zhutian/.conda/envs/infospace/lib/python3.6/site-packages/transformers/configuration_utils.py", line 362, in get_config_dict

raise EnvironmentError(msg)
OSError: Can't load config for 'cross-encoder/ms-marco-TinyBERT-L-6'. Make sure that:

Traceback (most recent call last):


 "src/spacy_load_vectors_bug.py", line 52, in <module>

tokens = client.gather(lambda_future)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/distributed/client.py", line 1967, in gather

asynchronous=asynchronous,


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/distributed/client.py", line 816, in sync

self.loop, func, *args, callback_timeout=callback_timeout, **kwargs


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/distributed/utils.py", line 347, in sync

raise exc.with_traceback(tb)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/distributed/utils.py", line 331, in f

result[0] = yield future


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/tornado/gen.py", line 735, in run

value = future.result()


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/distributed/client.py", line 1826, in _gather

raise exception.with_traceback(traceback)


 "src/spacy_load_vectors_bug.py", line 32, in extract_tokens

return [tok.lemma_ for tok in nlp(text) if not tok.is_punct]


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/spacy/language.py", line 439, in __call__

doc = proc(doc, **component_cfg.get(name, {}))


 "pipes.pyx", line 396, in spacy.pipeline.pipes.Tagger.__call__


 "pipes.pyx", line 415, in spacy.pipeline.pipes.Tagger.predict


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/neural/_classes/model.py", line 167, in __call__

return self.predict(x)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/neural/_classes/feed_forward.py", line 40, in predict

X = layer(X)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/neural/_classes/model.py", line 167, in __call__

return self.predict(x)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/api.py", line 310, in predict

X = layer(layer.ops.flatten(seqs_in, pad=pad))


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/neural/_classes/model.py", line 167, in __call__

return self.predict(x)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/neural/_classes/feed_forward.py", line 40, in predict

X = layer(X)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/neural/_classes/model.py", line 167, in __call__

return self.predict(x)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/neural/_classes/model.py", line 131, in predict

y, _ = self.begin_update(X, drop=None)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/api.py", line 379, in uniqued_fwd

Y_uniq, bp_Y_uniq = layer.begin_update(X_uniq, drop=drop)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/neural/_classes/feed_forward.py", line 46, in begin_update

X, inc_layer_grad = layer.begin_update(X, drop=drop)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/api.py", line 163, in begin_update

values = [fwd(X, *a, **k) for fwd in forward]


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/api.py", line 163, in <listcomp>

values = [fwd(X, *a, **k) for fwd in forward]


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/api.py", line 256, in wrap

output = func(*args, **kwargs)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/api.py", line 163, in begin_update

values = [fwd(X, *a, **k) for fwd in forward]


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/api.py", line 163, in <listcomp>

values = [fwd(X, *a, **k) for fwd in forward]


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/api.py", line 256, in wrap

output = func(*args, **kwargs)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/api.py", line 163, in begin_update

values = [fwd(X, *a, **k) for fwd in forward]


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/api.py", line 163, in <listcomp>

values = [fwd(X, *a, **k) for fwd in forward]


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/api.py", line 256, in wrap

output = func(*args, **kwargs)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/api.py", line 163, in begin_update

values = [fwd(X, *a, **k) for fwd in forward]


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/api.py", line 163, in <listcomp>

values = [fwd(X, *a, **k) for fwd in forward]


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/api.py", line 256, in wrap

output = func(*args, **kwargs)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/neural/_classes/static_vectors.py", line 60, in begin_update

vector_table = self.get_vectors()


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/neural/_classes/static_vectors.py", line 55, in get_vectors

return get_vectors(self.ops, self.lang)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/extra/load_nlp.py", line 26, in get_vectors

nlp = get_spacy(lang)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/thinc/extra/load_nlp.py", line 14, in get_spacy

SPACY_MODELS[lang] = spacy.load(lang, **kwargs)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/spacy/__init__.py", line 30, in load

return util.load_model(name, **overrides)


 "/opt/conda/envs/rapids/lib/python3.7/site-packages/spacy/util.py", line 169, in load_model

raise IOError(Errors.E050.format(name=name))
OSError: [E050] Can't find model 'en_core_sci_lg_vectors'. It doesn't seem to be a shortcut link, a Python package or a valid path to a data directory.
