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    print("Available tasks:")17    for name, prefix in model.prompts.items():18        print(f" {name}: \"{prefix}\"")19    print("-"*80)20    21    for sentence in [sentence_high, sentence_medium, sentence_low]:22        print("🙋‍♂️")23        print(sentence)24        embeddings = model.encode(sentence, prompt_name="STS")25        similarities = model.similarity(embeddings[0], embeddings[1])26        print("`-> 🤖 score: ", similarities.numpy()[0][0])27    with open('google_embeddinggemma-300m_5.txt', 'w', encoding='utf-8') as f:28        f.write('Everything was good in google_embeddinggemma-300m_5.txt')29except Exception as e:30    import os31    from slack_sdk import WebClient32    client = WebClient(token=os.environ['SLACK_TOKEN'])33    client.chat_postMessage(34        channel='#hub-model-metadata-snippets-sprint',35        text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/google_embeddinggemma-300m_5.txt|google_embeddinggemma-300m_5.txt>',36    )37 38    with open('google_embeddinggemma-300m_5.txt', 'a', encoding='utf-8') as f:39        import traceback40        f.write('''```CODE: 41print("Available tasks:")42for name, prefix in model.prompts.items():43    print(f" {name}: \"{prefix}\"")44print("-"*80)45 46for sentence in [sentence_high, sentence_medium, sentence_low]:47    print("🙋‍♂️")48    print(sentence)49    embeddings = model.encode(sentence, prompt_name="STS")50    similarities = model.similarity(embeddings[0], embeddings[1])51    print("`-> 🤖 score: ", similarities.numpy()[0][0])52```53 54ERROR: 55''')56        traceback.print_exc(file=f)57    58finally:59    from huggingface_hub import upload_file60    upload_file(61        path_or_fileobj='google_embeddinggemma-300m_5.txt',62        repo_id='model-metadata/code_execution_files',63        path_in_repo='google_embeddinggemma-300m_5.txt',64        repo_type='dataset',65    )66