ODQA on Wikipedia example doesn't work

Created by: zjohn77

Getting the error below when I try to follow the Quick Start from: http://docs.deeppavlov.ai/en/master/features/skills/odqa.html

My environment is: DeepPavlov 0.11.0, python 3.7.7, MacOS 10.15.5

FileNotFoundError Traceback (most recent call last) ~/my_pav.py in 2 from deeppavlov.core.commands.infer import build_model 3 ----> 4 odqa = build_model(configs.odqa.en_odqa_infer_wiki, load_trained=True) 5 6 result = odqa(['What is the name of Darth Vader's son?'])

~/opt/miniconda3/lib/python3.7/site-packages/deeppavlov/core/commands/infer.py in build_model(config, mode, load_trained, download, serialized) 60 component_serialized = None 61 ---> 62 component = from_params(component_config, mode=mode, serialized=component_serialized) 63 64 if 'id' in component_config:

~/opt/miniconda3/lib/python3.7/site-packages/deeppavlov/core/common/params.py in from_params(params, mode, serialized, **kwargs) 79 _refs.clear() 80 config = parse_config(expand_path(config_params['config_path'])) ---> 81 model = build_model(config, serialized=serialized) 82 _refs.clear() 83 _refs.update(refs)

~/opt/miniconda3/lib/python3.7/site-packages/deeppavlov/core/common/params.py in from_params(params, mode, serialized, **kwargs) 104 kwargs['mode'] = mode 105 --> 106 component = obj(**dict(config_params, **kwargs)) 107 try: 108 _refs[config_params['id']] = component

~/opt/miniconda3/lib/python3.7/site-packages/deeppavlov/models/vectorizers/hashing_tfidf_vectorizer.py in init(self, tokenizer, hash_size, doc_index, save_path, load_path, **kwargs) 78 79 if kwargs.get('mode', 'infer') == 'infer': ---> 80 self.tfidf_matrix, opts = self.load() 81 self.ngram_range = opts['ngram_range'] 82 self.hash_size = opts['hash_size']

~/opt/miniconda3/lib/python3.7/site-packages/deeppavlov/models/vectorizers/hashing_tfidf_vectorizer.py in load(self) 260 """ 261 if not self.load_path.exists(): --> 262 raise FileNotFoundError("HashingTfIdfVectorizer path doesn't exist!") 263 264 logger.info("Loading tfidf matrix from {}".format(self.load_path))

FileNotFoundError: HashingTfIdfVectorizer path doesn't exist!