model-metadata/code_python_files

1# /// script2# requires-python = ">=3.12"3# dependencies = [4#     "numpy",5#     "einops",6#     "pandas",7#     "matplotlib",8#     "protobuf",9#     "torch",10#     "sentencepiece",11#     "torchvision",12#     "transformers",13#     "timm",14#     "diffusers",15#     "sentence-transformers",16#     "accelerate",17#     "peft",18#     "slack-sdk",19# ]20# ///21 22try:23    import soundfile as sf24    from voxcpm import VoxCPM25    26    model = VoxCPM.from_pretrained("openbmb/VoxCPM1.5")27    28    wav = model.generate(29        text="VoxCPM is an innovative end-to-end TTS model from ModelBest, designed to generate highly expressive speech.",30        prompt_wav_path=None,      # optional: path to a prompt speech for voice cloning31        prompt_text=None,          # optional: reference text32        cfg_value=2.0,             # LM guidance on LocDiT, higher for better adherence to the prompt, but maybe worse33        inference_timesteps=10,   # LocDiT inference timesteps, higher for better result, lower for fast speed34        normalize=True,           # enable external TN tool35        denoise=True,             # enable external Denoise tool36        retry_badcase=True,        # enable retrying mode for some bad cases (unstoppable)37        retry_badcase_max_times=3,  # maximum retrying times38        retry_badcase_ratio_threshold=6.0, # maximum length restriction for bad case detection (simple but effective), it could be adjusted for slow pace speech39    )40    41    sf.write("output.wav", wav, 16000)42    print("saved: output.wav")43    with open('openbmb_VoxCPM1.5_0.txt', 'w', encoding='utf-8') as f:44        f.write('Everything was good in openbmb_VoxCPM1.5_0.txt')45except Exception as e:46    import os47    from slack_sdk import WebClient48    client = WebClient(token=os.environ['SLACK_TOKEN'])49    client.chat_postMessage(50        channel='#hub-model-metadata-snippets-sprint',51        text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/openbmb_VoxCPM1.5_0.txt|openbmb_VoxCPM1.5_0.txt>',52    )53 54    with open('openbmb_VoxCPM1.5_0.txt', 'a', encoding='utf-8') as f:55        import traceback56        f.write('''```CODE: 57import soundfile as sf58from voxcpm import VoxCPM59 60model = VoxCPM.from_pretrained("openbmb/VoxCPM1.5")61 62wav = model.generate(63    text="VoxCPM is an innovative end-to-end TTS model from ModelBest, designed to generate highly expressive speech.",64    prompt_wav_path=None,      # optional: path to a prompt speech for voice cloning65    prompt_text=None,          # optional: reference text66    cfg_value=2.0,             # LM guidance on LocDiT, higher for better adherence to the prompt, but maybe worse67    inference_timesteps=10,   # LocDiT inference timesteps, higher for better result, lower for fast speed68    normalize=True,           # enable external TN tool69    denoise=True,             # enable external Denoise tool70    retry_badcase=True,        # enable retrying mode for some bad cases (unstoppable)71    retry_badcase_max_times=3,  # maximum retrying times72    retry_badcase_ratio_threshold=6.0, # maximum length restriction for bad case detection (simple but effective), it could be adjusted for slow pace speech73)74 75sf.write("output.wav", wav, 16000)76print("saved: output.wav")77```78 79ERROR: 80''')81        traceback.print_exc(file=f)82    83finally:84    from huggingface_hub import upload_file85    upload_file(86        path_or_fileobj='openbmb_VoxCPM1.5_0.txt',87        repo_id='model-metadata/code_execution_files',88        path_in_repo='openbmb_VoxCPM1.5_0.txt',89        repo_type='dataset',90    )91