hope this fix your issue @rylan-feldspar's answer is generally the correct approach and will work, but you could do this a bit more compactly using standard Python libraries/idioms, especially itertools, a list-comprehension, and sorting functions.

For example, first use combinations() from itertools to generate all pairs of your candidate words:

```
from itertools import combinations
candidate_words = ['architect', 'nurse', 'surgeon', 'grandmother', 'dad']
all_pairs = combinations(candidate_words, 2)
```

```
scored_pairs = [(w2v_model.wv.similarity(p[0], p[1]), p)
for p in all_pairs]
```

```
sorted_pairs = sorted(scored_pairs, reverse=True)
print(sorted_pairs[0]) # first item is most-similar pair
```

```
print(sorted([(w2v_model.wv.similarity(p[0], p[1]), p)
for p in combinations(candidate_words, 2)
], reverse=True)[0])
```

```
print(max(combinations(candidate_words, 2),
key=lambda p:w2v_model.wv.similarity(p[0], p[1])))
```