I have the following list:
list1=[['brute-force',
'password-guessing',
'password-guessing',
'default-credentials',
'shell'],
['malware',
'ddos',
'phishing',
'spam',
'botnet',
'cryptojacking',
'xss',
'sqli',
'vulnerability'],
['sensitive-information']]
I am trying the example from here enter link description here
However when I am fitting my list to get the embeddings :
embeddings1 =sbert_model.encode(list1, convert_to_tensor=True)
I get the embeding i get the following error:
IndexError Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_16484/3954167634.py in <module>
----> 1 embeddings2 = sbert_model.encode(list3, convert_to_tensor=True)
~\anaconda3\envs\tensorflow_env\lib\site-packages\sentence_transformers\SentenceTransformer.py in encode(self, sentences, batch_size, show_progress_bar, output_value, convert_to_numpy, convert_to_tensor, device, normalize_embeddings)
159 for start_index in trange(0, len(sentences), batch_size, desc="Batches", disable=not show_progress_bar):
160 sentences_batch = sentences_sorted[start_index:start_index+batch_size]
--> 161 features = self.tokenize(sentences_batch)
162 features = batch_to_device(features, device)
163
~\anaconda3\envs\tensorflow_env\lib\site-packages\sentence_transformers\SentenceTransformer.py in tokenize(self, texts)
317 Tokenizes the texts
318 """
--> 319 return self._first_module().tokenize(texts)
320
321 def get_sentence_features(self, *features):
~\anaconda3\envs\tensorflow_env\lib\site-packages\sentence_transformers\models\Transformer.py in tokenize(self, texts)
101 for text_tuple in texts:
102 batch1.append(text_tuple[0])
--> 103 batch2.append(text_tuple[1])
104 to_tokenize = [batch1, batch2]
105
IndexError: list index out of range
I am understanding how lists work and I have read many asnwers to same problem in here but i cannot fiqure out why is going out of range.
Any ideas?