| ```CODE: | |
| def check_word_similarities(): | |
| # Calculate the embedding similarities | |
| print("similarity function: ", model.similarity_fn_name) | |
| similarities = model.similarity(embeddings[0], embeddings[1:]) | |
| print(similarities) | |
| for idx, word in enumerate(words[1:]): | |
| print("πββοΈ apple vs.", word, "-> π€ score: ", similarities.numpy()[0][idx]) | |
| # Calculate embeddings by calling model.encode() | |
| embeddings = model.encode(words, prompt_name="STS") | |
| check_word_similarities() | |
| ``` | |
| ERROR: | |
| Traceback (most recent call last): | |
| File "/tmp/google_embeddinggemma-300m_785mJ1M.py", line 24, in <module> | |
| embeddings = model.encode(words, prompt_name="STS") | |
| ^^^^^ | |
| NameError: name 'model' is not defined | |