Instructions to use DevParker/VibeVoice7b-low-vram with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- VibeVoice
How to use DevParker/VibeVoice7b-low-vram 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("DevParker/VibeVoice7b-low-vram") model = VibeVoiceForConditionalGenerationInference.from_pretrained( "DevParker/VibeVoice7b-low-vram", 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
Gradio UI for quantized vibevoice model
🔥 1
#5 opened 8 months ago
by
Mockreeze
When is the new fp8 version coming?
6
#4 opened 9 months ago
by
ca231321
where is the vibevoice python code?
#3 opened 9 months ago
by
asdasdf32
Request: DOI
👍🤝 3
2
#2 opened 9 months ago
by
Universe97
Noise with 8bit model
3
#1 opened 9 months ago
by
BahamutRU