I'm using EasyNMT for translating customer reviews. During translation, I got this error
HTTPError: 404 Client Error: Not Found for url: https://huggingface.co/api/models/Helsinki-NLP/opus-mt-ro-en
`HTTPError Traceback (most recent call last)
in
1 for index, row in df_review['AnswerValue'].iteritems():
----> 2 translated_row = model.translate(row, target_lang='en')#translating each row
3 df_review.loc[index, 'Translate'] = translated_row
~/opt/anaconda3/lib/python3.8/site-packages/easynmt/EasyNMT.py in translate(self, documents, target_lang, source_lang, show_progress_bar, beam_size, batch_size, perform_sentence_splitting, paragraph_split, sentence_splitter, document_language_detection, **kwargs)
152 except Exception as e:
153 logger.warning("Exception: "+str(e))
--> 154 raise e
155
156 if is_single_doc and len(output) == 1:
~/opt/anaconda3/lib/python3.8/site-packages/easynmt/EasyNMT.py in translate(self, documents, target_lang, source_lang, show_progress_bar, beam_size, batch_size, perform_sentence_splitting, paragraph_split, sentence_splitter, document_language_detection, **kwargs)
147 method_args['documents'] = [documents[idx] for idx in ids]
148 method_args['source_lang'] = lng
--> 149 translated = self.translate(**method_args)
150 for idx, translated_sentences in zip(ids, translated):
151 output[idx] = translated_sentences
~/opt/anaconda3/lib/python3.8/site-packages/easynmt/EasyNMT.py in translate(self, documents, target_lang, source_lang, show_progress_bar, beam_size, batch_size, perform_sentence_splitting, paragraph_split, sentence_splitter, document_language_detection, **kwargs)
179 #logger.info("Translate {} sentences".format(len(splitted_sentences)))
180
--> 181 translated_sentences = self.translate_sentences(splitted_sentences, target_lang=target_lang, source_lang=source_lang, show_progress_bar=show_progress_bar, beam_size=beam_size, batch_size=batch_size, **kwargs)
182
183 # Merge sentences back to documents
~/opt/anaconda3/lib/python3.8/site-packages/easynmt/EasyNMT.py in translate_sentences(self, sentences, target_lang, source_lang, show_progress_bar, beam_size, batch_size, **kwargs)
276
277 for start_idx in iterator:
--> 278 output.extend(self.translator.translate_sentences(sentences_sorted[start_idx:start_idx+batch_size], source_lang=source_lang, target_lang=target_lang, beam_size=beam_size, device=self.device, **kwargs))
279
280 #Restore original sorting of sentences
~/opt/anaconda3/lib/python3.8/site-packages/easynmt/models/OpusMT.py in translate_sentences(self, sentences, source_lang, target_lang, device, beam_size, **kwargs)
38 def translate_sentences(self, sentences: List[str], source_lang: str, target_lang: str, device: str, beam_size: int = 5, **kwargs):
39 model_name = 'Helsinki-NLP/opus-mt-{}-{}'.format(source_lang, target_lang)
---> 40 tokenizer, model = self.load_model(model_name)
41 model.to(device)
42
~/opt/anaconda3/lib/python3.8/site-packages/easynmt/models/OpusMT.py in load_model(self, model_name)
20 else:
21 logger.info("Load model: "+model_name)
---> 22 tokenizer = MarianTokenizer.from_pretrained(model_name)
23 model = MarianMTModel.from_pretrained(model_name)
24 model.eval()
~/opt/anaconda3/lib/python3.8/site-packages/transformers/tokenization_utils_base.py in from_pretrained(cls, pretrained_model_name_or_path, *init_inputs, **kwargs)
1645 else:
1646 # At this point pretrained_model_name_or_path is either a directory or a model identifier name
-> 1647 fast_tokenizer_file = get_fast_tokenizer_file(
1648 pretrained_model_name_or_path, revision=revision, use_auth_token=use_auth_token
1649 )
~/opt/anaconda3/lib/python3.8/site-packages/transformers/tokenization_utils_base.py in get_fast_tokenizer_file(path_or_repo, revision, use_auth_token)
3406 """
3407 # Inspect all files from the repo/folder.
-> 3408 all_files = get_list_of_files(path_or_repo, revision=revision, use_auth_token=use_auth_token)
3409 tokenizer_files_map = {}
3410 for file_name in all_files:
~/opt/anaconda3/lib/python3.8/site-packages/transformers/file_utils.py in get_list_of_files(path_or_repo, revision, use_auth_token)
1691 else:
1692 token = None
-> 1693 model_info = HfApi(endpoint=HUGGINGFACE_CO_RESOLVE_ENDPOINT).model_info(
1694 path_or_repo, revision=revision, token=token
1695 )
~/opt/anaconda3/lib/python3.8/site-packages/huggingface_hub/hf_api.py in model_info(self, repo_id, revision, token)
246 )
247 r = requests.get(path, headers=headers)
--> 248 r.raise_for_status()
249 d = r.json()
250 return ModelInfo(**d)
~/opt/anaconda3/lib/python3.8/site-packages/requests/models.py in raise_for_status(self)
941
942 if http_error_msg:
--> 943 raise HTTPError(http_error_msg, response=self)
944
945 def close(self):
HTTPError: 404 Client Error: Not Found for url: https://huggingface.co/api/models/Helsinki-NLP/opus-mt-ro-en`
Could you please review and fix the issue?
Thank you.
Hi,
I'm using EasyNMT for translating customer reviews. During translation, I got this error HTTPError: 404 Client Error: Not Found for url: https://huggingface.co/api/models/Helsinki-NLP/opus-mt-ro-en `HTTPError Traceback (most recent call last)