KugelAudio-0-Open GGUF
GGUF conversions of kugelaudio/kugelaudio-0-open for use with CrispASR.
Files
| File | Quant | Size | Notes |
|---|---|---|---|
kugelaudio-0-open-f16.gguf | F16 | 16.1 GB | Full precision, inference-only (no encoders) |
kugelaudio-0-open-q4_k.gguf | Q4_K | 5.3 GB | 4-bit quantized, inference-only (no encoders) |
Both files contain the inference-only components (--no-encoders): Qwen2.5-7B language model, 4-layer DiT diffusion head, acoustic connector, and acoustic VAE decoder. Encoder weights (for voice cloning from raw audio) are omitted since the open-source release only supports pre-encoded voices.
Architecture
Text → Qwen2.5-7B (28L, 3584d, GQA 28/4)
→ AR decode with constrained token set
→ 4-layer DiT diffusion head (AdaLN, SwiGLU, v-prediction)
→ 20-step SDE-DPMSolver++ (cosine beta schedule)
→ Acoustic VAE decoder (6-stage ConvNeXt, 3200x upsample)
→ 24 kHz mono PCM
- 23 languages: en, de, fr, es, it, pt, nl, pl, ru, uk, cs, ro, hu, sv, da, fi, no, el, bg, sk, hr, sr, tr
- License: MIT
- Output: 24 kHz mono PCM
- Classifier-free guidance: cfg_scale=3.0 (default)
Usage with CrispASR
# Synthesize speech
crispasr --backend kugelaudio \
-m kugelaudio-0-open-q4_k.gguf \
--tts "Hello, this is a test of the speech synthesis system." \
--tts-output output.wav
# With auto-download
crispasr --backend kugelaudio -m auto \
--tts "Hallo, dies ist ein Test." -l de
Conversion
Converted with:
python models/convert-kugelaudio-to-gguf.py \
--input kugelaudio/kugelaudio-0-open \
--output kugelaudio-0-open-f16.gguf \
--no-encoders --type f16
crispasr-quantize kugelaudio-0-open-f16.gguf kugelaudio-0-open-q4_k.gguf q4_k
Original Model
- Paper/repo: kugelaudio/kugelaudio-0-open
- Architecture: Based on Microsoft VibeVoice — hybrid AR + diffusion TTS
- Parameters: ~7B (Qwen2.5-7B backbone)
- Training data: Undisclosed
- License: MIT