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developerjeremylive/vibevoice-1.5b-GGUF-etheroi

sourceHugging Facemitupdated 4mo agoView on Hugging Face
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Model Card

VibeVoice-1.5B GGUF

GGUF conversion of microsoft/VibeVoice-1.5B for use with CrispASR.

This is the base model (not the streaming variant). It supports voice cloning from audio samples and multi-speaker synthesis.

Model variants

FileQuantSizeNotes
vibevoice-1.5b-tts-f16.ggufF165.1 GBFull precision
vibevoice-1.5b-tts-q8_0.ggufQ8_02.8 GBNear-lossless
vibevoice-1.5b-tts-q4_k.ggufQ4_K1.6 GBSmallest, perfect ASR round-trip

Usage

Requires a voice reference audio (WAV file, 24 kHz mono) for voice cloning:

bash
# Voice cloning TTS
VIBEVOICE_VOICE_AUDIO=reference_voice.wav \
crispasr --tts "Hello, how are you today?" \
    -m vibevoice-1.5b-tts-q4_k.gguf \
    --tts-output output.wav

Architecture

Single-LM architecture (differs from the streaming Realtime-0.5B):

  • —LM: Qwen2.5-1.5B (d=1536, 28 layers, 12 heads, 2 KV heads)
  • —Prediction head: 4 AdaLN + SwiGLU layers (d=1536)
  • —Acoustic encoder: 7-stage ConvNeXt (3200x downsample from 24kHz)
  • —Semantic encoder: same architecture, 128-dim latent
  • —Decoder: 7-stage transposed ConvNeXt (3200x upsample)
  • —DPM-Solver++: 20-step, cosine schedule, v-prediction

The model generates speech tokens autoregressively — the LM produces <|vision_pad|> (speechdiffusion) tokens that trigger diffusion sampling, with `<|visionstart|> / <|vision_end|>` as control tokens.

Quality

InputParakeet ASR
"Hello, how are you today?""Hello, how are you today?"

Differences from Realtime-0.5B

FeatureRealtime-0.5B1.5B Base
Architecture4L base + 20L TTS LMSingle 28L LM
Voice inputPre-computed .pt promptsAudio WAV files
Voice cloningNo (fixed presets)Yes (from reference audio)
Multi-speakerNoYes (up to 4 speakers)
StreamingYesNo

License

MIT (same as original model).