model-metadata/code_python_files

1# /// script2# requires-python = ">=3.12"3# dependencies = [4#     "torch",5#     "torchvision",6#     "transformers",7#     "diffusers",8#     "sentence-transformers",9#     "accelerate",10#     "peft",11#     "slack-sdk",12# ]13# ///14 15try:16    def check_word_similarities():17        # Calculate the embedding similarities18        print("similarity function: ", model.similarity_fn_name)19        similarities = model.similarity(embeddings[0], embeddings[1:])20        print(similarities)21    22        for idx, word in enumerate(words[1:]):23            print("🙋‍♂️ apple vs.", word, "-> 🤖 score: ", similarities.numpy()[0][idx])24    25    # Calculate embeddings by calling model.encode()26    embeddings = model.encode(words, prompt_name="STS")27    28    check_word_similarities()29    with open('google_embeddinggemma-300m_7.txt', 'w', encoding='utf-8') as f:30        f.write('Everything was good in google_embeddinggemma-300m_7.txt')31except Exception as e:32    import os33    from slack_sdk import WebClient34    client = WebClient(token=os.environ['SLACK_TOKEN'])35    client.chat_postMessage(36        channel='#hub-model-metadata-snippets-sprint',37        text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/google_embeddinggemma-300m_7.txt|google_embeddinggemma-300m_7.txt>',38    )39 40    with open('google_embeddinggemma-300m_7.txt', 'a', encoding='utf-8') as f:41        import traceback42        f.write('''```CODE: 43def check_word_similarities():44    # Calculate the embedding similarities45    print("similarity function: ", model.similarity_fn_name)46    similarities = model.similarity(embeddings[0], embeddings[1:])47    print(similarities)48 49    for idx, word in enumerate(words[1:]):50        print("🙋‍♂️ apple vs.", word, "-> 🤖 score: ", similarities.numpy()[0][idx])51 52# Calculate embeddings by calling model.encode()53embeddings = model.encode(words, prompt_name="STS")54 55check_word_similarities()56```57 58ERROR: 59''')60        traceback.print_exc(file=f)61    62finally:63    from huggingface_hub import upload_file64    upload_file(65        path_or_fileobj='google_embeddinggemma-300m_7.txt',66        repo_id='model-metadata/code_execution_files',67        path_in_repo='google_embeddinggemma-300m_7.txt',68        repo_type='dataset',69    )70