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BuckyBalls
/
chainsaw-voice-lora

VibeVoice
Safetensors
lora
tts
Model card Files Files and versions
xet
Community

Instructions to use BuckyBalls/chainsaw-voice-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • VibeVoice

    How to use BuckyBalls/chainsaw-voice-lora with VibeVoice:

    import torch, soundfile as sf, librosa, numpy as np
    from vibevoice.processor.vibevoice_processor import VibeVoiceProcessor
    from vibevoice.modular.modeling_vibevoice_inference import VibeVoiceForConditionalGenerationInference
    
    # Load voice sample (should be 24kHz mono)
    voice, sr = sf.read("path/to/voice_sample.wav")
    if voice.ndim > 1: voice = voice.mean(axis=1)
    if sr != 24000: voice = librosa.resample(voice, sr, 24000)
    
    processor = VibeVoiceProcessor.from_pretrained("BuckyBalls/chainsaw-voice-lora")
    model = VibeVoiceForConditionalGenerationInference.from_pretrained(
        "BuckyBalls/chainsaw-voice-lora", torch_dtype=torch.bfloat16
    ).to("cuda").eval()
    model.set_ddpm_inference_steps(5)
    
    inputs = processor(text=["Speaker 0: Hello!\nSpeaker 1: Hi there!"],
                       voice_samples=[[voice]], return_tensors="pt")
    audio = model.generate(**inputs, cfg_scale=1.3,
                           tokenizer=processor.tokenizer).speech_outputs[0]
    sf.write("output.wav", audio.cpu().numpy().squeeze(), 24000)
  • Notebooks
  • Google Colab
  • Kaggle
chainsaw-voice-lora
824 MB
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  • 1 contributor
History: 2 commits
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BuckyBalls
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e4d3512 verified about 2 months ago
  • acoustic_connector
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  • semantic_connector
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  • .gitattributes
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  • README.md
    153 Bytes
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  • adapter_config.json
    1.03 kB
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  • adapter_model.safetensors
    73.9 MB
    xet
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  • diffusion_head_full.bin

    Detected Pickle imports (3)

    • "torch._utils._rebuild_tensor_v2",
    • "collections.OrderedDict",
    • "torch.BFloat16Storage"

    What is a pickle import?

    247 MB
    xet
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